Chemically Guided Ambient Ionisation Mass Spectrometry

ABSTRACT

A method is disclosed comprising obtaining or acquiring chemical or other non-mass spectrometric data from one or more regions of a target ( 2 ) using a chemical sensor ( 20 ). The chemical or other non-mass spectrometric data may be used to determine one or more regions of interest of the target ( 2 ). An ambient ionisation ion source  1  may then be used to generate aerosol, smoke or vapour ( 5 ) from one or more regions of the target ( 2 ).

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority from and the benefit of United Kingdompatent application No. 1503876.3 filed on 6 Mar. 2015, United Kingdompatent application No. 1503864.9 filed on 6 Mar. 2015, United Kingdompatent application No. 1518369.2 filed on 16 Oct. 2015, United Kingdompatent application No. 1503877.1 filed on 6 Mar. 2015, United Kingdompatent application No. 1503867.2 filed on 6 Mar. 2015, United Kingdompatent application No. 1503863.1 filed on 6 Mar. 2015, United Kingdompatent application No. 1503878.9 filed on 6 Mar. 2015, United Kingdompatent application No. 1503879.7 filed on 6 Mar. 2015 and United Kingdompatent application No. 1516003.9 filed on 9 Sep. 2015. The entirecontents of these applications are incorporated herein by reference.

FIELD OF THE INVENTION

The present invention relates generally to the analysis of a target(which may, for example, comprise in vivo, ex vivo or in vitrobiological tissue, a bacterial or fungal colony or more generally anorganic target such as a plastic) by ambient ionisation techniques suchas rapid evaporative ionisation mass spectrometry (“REIMS”), methods ofanalysis and diagnosis and apparatus for analysing a target using anambient ionisation ion source. Various embodiments are contemplatedwherein analyte ions generated by an ambient ionisation ion source arethen subjected either to: (i) mass analysis by a mass analyser such as aquadrupole mass analyser or a Time of Flight mass analyser; (ii) ionmobility analysis (IMS) and/or differential ion mobility analysis (DMA)and/or Field Asymmetric Ion Mobility Spectrometry (FAIMS) analysis;and/or (iii) a combination of firstly ion mobility analysis (IMS) and/ordifferential ion mobility analysis (DMA) and/or Field Asymmetric IonMobility Spectrometry (FAIMS) analysis followed by secondly massanalysis by a mass analyser such as a quadrupole mass analyser or a Timeof Flight mass analyser (or vice versa). Various embodiments also relateto an ion mobility spectrometer and/or mass analyser and a method of ionmobility spectrometry and/or method of mass analysis.

BACKGROUND

Rapid evaporative ionisation mass spectrometry (“REIMS”) is a relativelynew technique that is useful for the analysis of many different types ofsamples including the identification of tissue.

Reference is made to N. Strittmatter et al., Anal. Chem. 2014, 86,6555-6562 which discloses an investigation into the suitability of usingrapid evaporative ionisation mass spectrometry as a generalidentification system for bacteria and fungi.

The known approach for analysing bacterial colonies by rapid evaporativeionisation mass spectrometry involves using bipolar electrosurgicalforceps and an electrosurgical RF generator. A bacterial colony isscraped from the surface of an agar layer using the bipolarelectrosurgical forceps and a short burst of RF voltage from theelectrosurgical RF generator is applied between the bipolarelectrosurgical forceps. For example, it is known to apply 60 W of powerin a bipolar mode at a frequency of 470 kHz sinusoid. The RF voltagewhich is applied to the electrosurgical forceps has the result ofrapidly heating the particular portion of the bacterial colony which isbeing analysed due to its nonzero impedance. The rapid heating of themicrobial mass results in an aerosol being generated. The aerosol istransferred directly into a mass spectrometer and the aerosol sample maythen be analysed by the mass spectrometer. It is known for the controlsystem of the mass spectrometer to utilise multivariate statisticalanalysis in order to help distinguish and identify different samples.

Brain cancers are one of the leading causes of cancer-related deaths inchildren and young adults. Surgical resection of primary brain tumoursis still the most often used therapy. However, in many cases thecomplete removal of the cancer is very difficult without damaging avital function and it is problematic to accurately determine the marginsof cancerous tissue when performing a resection of a brain tumour.

It is desired to provide an improved method of analysing a target ortissue using an ambient ionisation ion source.

SUMMARY

According to an aspect there is provided a method comprising:

obtaining or acquiring chemical or other non-mass spectrometric datafrom one or more regions of a target; and

using a first device to generate aerosol, smoke or vapour from one ormore regions of the target.

A workflow has been developed which uses an optical method (such asRaman spectroscopy) followed by a mass spectrometry based method (suchas rapid evaporative ionisation mass spectrometry (“REIMS”)) for cancertissue identification within an operating theatre or other environments.

Raman spectroscopy is a non-invasive laser based method which probes themolecular vibrations and excitations of molecules within a target (e.g.,tissue).

In particular, various embodiments are disclosed which relate to thecombination of Raman spectroscopy and rapid evaporative ionisation massspectrometry in the context of brain surgery. The approach may bevalidated by, for example, using an in vivo three dimensional ultrasonicneuronavigational system together with conventional histopathology.Various three dimensional ultrasonic neuronavigational systems are knownincluding SonoWand® and such navigational systems may be utilisedaccording to various embodiments.

Experimental results are presented which demonstrate how the combinationof rapid evaporative ionisation mass spectrometry (“REIMS”) togetherwith Raman spectroscopy enables a high degree of tissue specificity tobe achieved especially by analysing the tissue sample in thephospholipid region.

The various embodiments which are disclosed enable healthy tissue to beaccurately distinguished from cancerous tissue and in particular enabledifferent brain cancers to be accurately determined during an operation.The combination of Raman spectroscopy and rapid evaporative ionisationmass spectrometry (“REIMS”) is particularly beneficial as it enablesimportant information to be provided to a surgeon and the disclosedtechnique is beneficial in the assessment of tumour margins which canbeneficially lead to an increase in the survival rate of patients.

Further details of a combined Raman spectroscopy and rapid evaporativeionisation mass spectrometry (“REIMS”) method for the in situidentification of brain tumours during surgery are disclosed below.

Although the following disclosure relates inter alia to improvements inthe assessment of tumour margins during brain surgery, it should beunderstood that further embodiments are contemplated wherein other partsof the body or other organs may be sampled using Raman spectroscopy (oranother chemical sensing method) followed by analysis using an ambiention source such as a rapid evaporative ionisation mass spectrometry(“REIMS”) ion source. In particular, it should be understood thatambient ionisation ion sources other than a rapid evaporative ionisationmass spectrometry (“REIMS”) ion source may be used.

In accordance with various embodiments chemical data may be acquiredfrom a target (which may comprise in vivo, ex vivo or in vitrobiological tissue, a bacterial or fungal colony or a more generalorganic target such as a plastic).

The method may further comprise using the chemical or other non-massspectrometric data to determine one or more regions of interest of thetarget.

The chemical or other non-mass spectrometric data may comprise dataselected from the group consisting of: (i) Raman spectroscopy data; (ii)chemical composition data; (iii) fluorescence data; (iv) absorptiondata; (v) reflectance data; (vi) transmission data; (vii) elasticscattering data; (viii) Fourier Transform Infra-Red Spectroscopy (FTIR)data; and (ix) interferometry data.

The first device may comprise or form part of an ambient ion orionisation source or the first device may generate the aerosol, smoke orvapour for subsequent ionisation by an ambient ion or ionisation sourceor other ionisation source.

The target may comprise native or unmodified target material.

The native or unmodified target material may be unmodified by theaddition of a matrix or reagent.

The first device may be arranged and adapted to generate aerosol, smokeor vapour from one or more regions of the target without the targetrequiring prior preparation.

The first device may comprise an ion source selected from the groupconsisting of: (i) a rapid evaporative ionisation mass spectrometry(“REIMS”) ion source; (ii) a desorption electrospray ionisation (“DESI”)ion source; (iii) a laser desorption ionisation (“LDI”) ion source; (iv)a thermal desorption ion source; (v) a laser diode thermal desorption(“LDTD”) ion source; (vi) a desorption electro-flow focusing (“DEFFI”)ion source; (vii) a dielectric barrier discharge (“DBD”) plasma ionsource; (viii) an Atmospheric Solids Analysis Probe (“ASAP”) ion source;(ix) an ultrasonic assisted spray ionisation ion source; (x) an easyambient sonic-spray ionisation (“EASI”) ion source; (xi) a desorptionatmospheric pressure photoionisation (“DAPPI”) ion source; (xii) apaperspray (“PS”) ion source; (xiii) a jet desorption ionisation(“JeDI”) ion source; (xiv) a touch spray (“TS”) ion source; (xv) anano-DESI ion source; (xvi) a laser ablation electrospray (“LAESI”) ionsource; (xvii) a direct analysis in real time (“DART”) ion source;(xviii) a probe electrospray ionisation (“PESI”) ion source; (xix) asolid-probe assisted electrospray ionisation (“SPA-ESI”) ion source;(xx) a cavitron ultrasonic surgical aspirator (“CUSA”) device; (xxi) afocussed or unfocussed ultrasonic ablation device; (xxii) a microwaveresonance device; and (xxiii) a pulsed plasma RF dissection device.

The step of using the first device to generate aerosol, smoke or vapourfrom one or more regions of the target further may comprise contactingthe target with one or more electrodes.

The one or more electrodes may comprise a bipolar device or a monopolardevice.

The one or more electrodes may comprise a rapid evaporation ionizationmass spectrometry (“REIMS”) device.

The method may further comprise applying an AC or RF voltage to the oneor more electrodes in order to generate the aerosol, smoke or vapour.

The step of applying the AC or RF voltage to the one or more electrodesmay comprise applying one or more pulses of the AC or RF voltage to theone or more electrodes.

The step of applying the AC or RF voltage to the one or more electrodesmay cause heat to be dissipated into the target.

The step of using the first device to generate aerosol, smoke or vapourfrom one or more regions of the target further may comprise irradiatingthe target with a laser.

The first device may be arranged and adapted to generate aerosol fromone or more regions of the target by direct evaporation or vaporisationof target material from the target by Joule heating or diathermy.

The step of using the first device to generate aerosol, smoke or vapourfrom one or more regions of the target further may comprise directingultrasonic energy into the target.

The aerosol may comprise uncharged aqueous droplets optionallycomprising cellular material.

At least 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95% of the massor matter generated by the first device and which forms the aerosol maybe in the form of droplets.

The first device may be arranged and adapted to generate aerosol whereinthe Sauter mean diameter (“SMD”, d32) of the aerosol may be in a range:(i)<5 μm; (ii) 5-10 μm; (iii) 10-15 μm; (iv) 15-20 μm; (v) 20-25 μm; or(vi) >25 μm.

The aerosol may traverse a flow region with a Reynolds number (Re) inthe range: (i)<2000; (ii) 2000-2500; (iii) 2500-3000; (iv) 3000-3500;(v) 3500-4000; or (vi) >4000.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a Weber number (We) selected from the groupconsisting of: (i)<50; (ii) 50-100; (iii) 100-150; (iv) 150-200; (v)200-250; (vi) 250-300; (vii) 300-350; (viii) 350-400; (ix) 400-450; (x)450-500; (xi) 500-550; (xii) 550-600; (xiii) 600-650; (xiv) 650-700;(xv) 700-750; (xvi) 750-800; (xvii) 800-850; (xviii) 850-900; (xix)900-950; (xx) 950-1000; and (xxi) >1000.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a Stokes number (S_(k)) in the range: (i) 1-5;(ii) 5-10; (iii) 10-15; (iv) 15-20; (v) 20-25; (vi) 25-30; (vii) 30-35;(viii) 35-40; (ix) 40-45; (x) 45-50; and (xi) >50.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a mean axial velocity selected from the groupconsisting of: (i)<20 m/s; (ii) 20-30 m/s; (iii) 30-40 m/s; (iv) 40-50m/s; (v) 50-60 m/s; (vi) 60-70 m/s; (vii) 70-80 m/s; (viii) 80-90 m/s;(ix) 90-100 m/s; (x) 100-110 m/s; (xi) 110-120 m/s; (xii) 120-130 m/s;(xiii) 130-140 m/s; (xiv) 140-150 m/s; and (xv) >150 m/s.

The target may comprise biological tissue, biological matter, abacterial colony or a fungal colony.

The biological tissue may comprise human tissue or non-human animaltissue.

The biological tissue may comprise in vivo biological tissue.

The biological tissue may comprise ex vivo biological tissue.

The biological tissue may comprise in vitro biological tissue.

The biological tissue may comprise: (i) adrenal gland tissue, appendixtissue, bladder tissue, bone, bowel tissue, brain tissue, breast tissue,bronchi, coronal tissue, ear tissue, esophagus tissue, eye tissue, gallbladder tissue, genital tissue, heart tissue, hypothalamus tissue,kidney tissue, large intestine tissue, intestinal tissue, larynx tissue,liver tissue, lung tissue, lymph nodes, mouth tissue, nose tissue,pancreatic tissue, parathyroid gland tissue, pituitary gland tissue,prostate tissue, rectal tissue, salivary gland tissue, skeletal muscletissue, skin tissue, small intestine tissue, spinal cord, spleen tissue,stomach tissue, thymus gland tissue, trachea tissue, thyroid tissue,ureter tissue, urethra tissue, soft and connective tissue, peritonealtissue, blood vessel tissue and/or fat tissue; (ii) grade I, grade II,grade III or grade IV cancerous tissue; (iii) metastatic canceroustissue; (iv) mixed grade cancerous tissue; (v) a sub-grade canceroustissue; (vi) healthy or normal tissue; or (vii) cancerous or abnormaltissue.

The first device may comprise a point of care (“POC”), diagnostic orsurgical device.

The method may further comprise ionising at least some of the aerosol,smoke or vapour so as to generate analyte ions.

The method may further comprise directing or aspirating at least some ofthe aerosol, smoke or vapour into a vacuum chamber of a massspectrometer.

The method may further comprise ionising at least some the aerosol,smoke or vapour within a or the vacuum chamber of the mass spectrometerso as to generate a plurality of analyte ions.

The method may further comprise causing the aerosol, smoke or vapour toimpact upon a collision surface located within a vacuum chamber of themass spectrometer so as to generate a plurality of analyte ions.

The method may further comprise mass analysing and/or ion mobilityanalysing the analyte ions in order to obtain mass spectrometric dataand/or ion mobility data.

Various embodiments are contemplated wherein analyte ions generated byan ambient ionisation ion source are then subjected either to: (i) massanalysis by a mass analyser such as a quadrupole mass analyser or a Timeof Flight mass analyser; (ii) ion mobility analysis (IMS) and/ordifferential ion mobility analysis (DMA) and/or Field Asymmetric IonMobility Spectrometry (FAIMS) analysis; and/or (iii) a combination offirstly ion mobility analysis (IMS) and/or differential ion mobilityanalysis (DMA) and/or Field Asymmetric Ion Mobility Spectrometry (FAIMS)analysis followed by secondly mass analysis by a mass analyser such as aquadrupole mass analyser or a Time of Flight mass analyser (or viceversa). Various embodiments also relate to an ion mobility spectrometerand/or mass analyser and a method of ion mobility spectrometry and/ormethod of mass analysis.

The method may further comprise mass analysing and/or ion mobilityanalysing the aerosol, smoke or vapour or ions derived from the aerosol,smoke or vapour in order to obtain mass spectrometric data and/or ionmobility data.

The method may further comprise analysing the mass spectrometric dataand/or ion mobility data in order either: (i) to distinguish betweenhealthy and diseased tissue; (ii) to distinguish between potentiallycancerous and non-cancerous tissue; (iii) to distinguish betweendifferent types or grades of cancerous tissue; (iv) to distinguishbetween different types or classes of target material; (v) to determinewhether or not one or more desired or undesired substances are presentin the target; (vi) to confirm the identity or authenticity of thetarget; (vii) to determine whether or not one or more impurities,illegal substances or undesired substances are present in the target;(viii) to determine whether a human or animal patient may be at anincreased risk of suffering an adverse outcome; (ix) to make or assistin the making a diagnosis or prognosis; and (x) to inform a surgeon,nurse, medic or robot of a medical, surgical or diagnostic outcome.

The step of analysing the mass spectrometric data and/or ion mobilitydata may comprise performing a supervised or unsupervised multivariatestatistical analysis of the mass spectrometric data and/or ion mobilitydata.

The multivariate statistical analysis may be selected from the groupconsisting of: (i) principal component analysis (“PCA”); and (ii) lineardiscriminant analysis (“LDA”).

The step of analysing the mass spectrometric data and/or ion mobilitydata may further comprise analysing a profile of the aerosol, smoke orvapour or a profile of ions derived from the aerosol, smoke or vapour.

The profile may be selected from the group consisting of: (i) alipidomic profile; (ii) a fatty acid profile; (iii) a phospholipidprofile; (iv) a phosphatidic acid (PA) profile; (v) aphosphatidylethanolamine (PE) profile; (vi) a phosphatidylglycerol (PG)profile; (vii) a phosphatidylserines (PS) profile; (viii) aphosphatidylinositol (PI) profile; or (ix) a triglyceride (TG) profile.

The method may further comprise using one or more Raman spectroscopysensors, detectors or devices to obtain the chemical or other non-massspectrometric data.

The method may further comprise determining the intensity of Ramanscattered light as a function of wavenumber.

The method may further comprise analysing Raman spectroscopy data inorder to determine data relating to vibrations of molecular bondspresent within the target.

The method may further comprise using the one or more Raman spectroscopysensors, detectors or devices to obtain the chemical or other non-massspectrometric data with or without the one or more Raman spectroscopysensors, detectors or devices physically contacting the target.

The method may further comprise determining a Raman spectrum or Ramanprofile of one or more regions of the target.

The method may further comprise using the chemical or other non-massspectrometric data to determine one or more regions of interest of thetarget by determining one or more regions of the target which have adifferent Raman spectrum, Raman profile or Raman spectral featurerelative to normal tissue, surrounding tissue, a control sample, acontrol region, control data or predetermined data.

The method may further comprise using the chemical or other non-massspectrometric data to determine one or more regions of interest of thetarget by determining whether or not a region of the target has a higheror lower Raman peak intensity relative to normal tissue, surroundingtissue, a control sample, a control region, control data orpredetermined data.

The method may further comprise directing light or ultra-violetradiation on to the target.

The ultra-violet radiation may have a wavelength in a range selectedfrom the group consisting of: (i) 100-150 nm; (ii) 150-200 nm; (iii)200-250 nm; (iv) 250-300 nm; (v) 300-350 nm; and (vi) 350-400 nm.

The method may further comprise detecting light or electromagneticradiation emitted from the target.

The method may further comprise determining a fluorescence orautofluorescence profile or spectrum.

The fluorescence or autofluorescence profile or spectrum may comprise ameasure of the intensity of light or electromagnetic radiation emittedfrom the target as a function of frequency or wavelength.

The method may further comprise comparing a fluorescence orautofluorescence profile or spectrum relating to a region of the targetwith a fluorescence or autofluorescence profile or spectrum obtainedfrom a control sample, a control region, control data or predetermineddata in order to determining one or more regions of interest of thetarget.

The method may further comprise directing light or infra-red radiationon to the target.

The light or infra-red radiation may have a wavelength in a rangeselected from the group consisting of: (i) 400-450 nm; (ii) 450-500 nm;(iii) 500-550 nm; (iv) 550-600 nm; (v) 600-650 nm; (vi) 650-700 nm;(vii) 700-750 nm; (viii) 750-800 nm; (ix) 800-850 nm; (x) 850-900 nm;(xi) 900-950 nm; (xii) 950-1000 nm; (xiii) 1000-1100 nm; (xiv) 1100-1200nm; (xv) 1200-1300 nm; (xvi) 1300-1400 nm; (xvii) 1400-1500 nm; (xviii)1500-1600 nm; (xix) 1600-1700 nm; (xx) 1700-1800 nm; (xxi) 1800-1900 nm;(xxii) 1900-2000 nm; (xxiii) 2000-2100 nm; (xxiv) 2100-2200 nm; (xxv)2200-2300 nm; (xxvi) 2300-2400 nm; (xxvii) 2400-2500 nm; (xxviii)2500-2600 nm; (xxix) 2600-2700 nm; (xxx) 2700-2800 nm; (xxxi) 2800-2900nm; and (xxxii) 2900-3000 nm.

The method may further comprise directing white light on to the target.

The method may further comprise detecting light or infra-red radiationreflected by or from the target.

The method may further comprise determining an absorbance, transmissionor reflectance profile or spectrum of a region of the target.

The absorbance, transmission or reflectance profile or spectrum maycomprise a measure of the intensity of light absorbed by, transmitted byor reflected by the target as a function of frequency or wavelength.

The method may further comprise comparing an absorbance, transmission orreflectance profile or spectrum relating to a region of the target withan absorbance, transmission or reflectance profile or spectrum obtainedfrom a control sample, a control region, control data or predetermineddata in order to determine one or more regions of interest of thetarget.

The method may further comprise directing ultra-violet radiation, lightor infra-red radiation on to the target.

The method may further comprise directing ultra-violet radiation, lightor infra-red radiation on to the target in order to produce aninterferogram as used in FTIR. Additionally or alternatively the methodmay comprise the application of an IR-transparent material such as KBrinto one of the analysis beams to increase the optical path length.

The ultra-violet radiation, light or infra-red radiation may have awavelength in a range selected from the group consisting of: (i) 300-350nm; (ii) 350-400 nm; (iii) 400-450 nm; (iv) 450-500 nm; (v) 500-500 nm;(vi) 500-550 nm; (vii) 550-600 nm; (viii) 600-650 nm; (ix) 650-700 nm;(x) 700-750 nm; (xi) 750-800 nm; (xii) 800-850 nm; (xiii) 850-900 nm;(xiv) 900-950 nm; (xv) 950-1000 nm; (xvi) 1000-1100 nm; (xvii) 1100-1200nm; (xviii) 1200-1300 nm; (xix) 1300-1400 nm; (xx) 1400-1500 nm; (xxi)1500-1600 nm; (xxii) 1600-1700 nm; (xxiii) 1700-1800 nm; (xxiv)1800-1900 nm; (xxv) 1900-2000 nm; (xxvi) 2000-2100 nm; (xxvii) 2100-2200nm; (xxviii) 2200-2300 nm; (xxix) 2300-2400 nm; (xxx) 2400-2500 nm;(xxxi) 2500-2600 nm; (xxxii) 2600-2700 nm; (xxxiii) 2700-2800 nm;(xxxiv) 2800-2900 nm; and (xxxv) 2900-3000 nm.

The method may further comprise directing white light on to the target.

The method may further comprise detecting ultra-violet radiation, lightor infra-red radiation reflected or scattered by the target.

The method may further comprise determining a scattered light intensityprofile or spectrum of a region of the target.

The scattered light intensity profile or spectrum may comprise a measureof the intensity of light scattered by the target as a function offrequency or wavelength.

The step of determining from the chemical or other non-massspectrometric data one or more regions of interest of the target maycomprise comparing a scattered light intensity profile or spectrumrelating to a region of the target with a scattered light intensityprofile or spectrum obtained from a control sample, a control region,control data or predetermined data.

The method may further comprise using the chemical or other non-massspectrometric data to determine the margins or bounds of one or moreregions of interest of the target.

The one or more regions of interest may comprise cancerous biologicaltissue or a tumour.

The cancerous biological tissue or the tumour may comprise either: (i)grade I, grade II, grade III or grade IV cancerous tissue; (ii)metastatic cancerous tissue; (iii) mixed grade cancerous tissue; or (iv)a sub-grade cancerous tissue.

The method may further comprise determining from the chemical or othernon-mass spectrometric data either: (i) one or more physical propertiesof the target; (ii) one or more chemical properties of the target; (iii)one or more physico-chemical properties of the target; or (iv) one ormore mechanical properties of the target.

The method may further comprise using one or more contrast agents toenhance the chemical data which is acquired.

The one or more contrast agents may comprise one or more fluorescentcontrast agents.

The one or more contrast agents may comprise one or more visible dyes.

The one or more contrast agents may comprise one or more radiocontrastagents.

The one or more contrast agents may comprise one or more optical, nearinfrared (“NIR”), fluorescent, autofluorescent or diagnostic contrastagents.

The one or more contrast agents may be selected from the groupconsisting of: (i) indocyanine green (“ICG”) and derivatives orconjugates of indocyanine green including indotricarbocyanine; (ii)diethylthiatricarbocyanine iodide (“DTTCI”) and derivatives orconjugates of diethylthiatricarbocyanine iodide; (iii) rhodamine B andderivatives or conjugates of rhodamine B; (iv) photodynamic therapy(“PDT”) agents including hexylpyropheophorbide (“HPPH”); (v) a cyaninedye including Cy 5.5 dyes; and (vi) bifunctional contrast agents.

The one or more contrast agents may comprise nanoparticles.

The one or more contrast agents may comprise: (i) magnetic orferromagnetic nanoparticles; (ii) gold nanoparticles; (iii) metallicnanoparticles; (iv) functionalised nanoparticles; (v) nanospheres,nanorods, nanostars or nanoshells; (vi) levan nanoparticles; or (vii)copper, zinc, titanium, magnesium, alginate, alloy or silvernanoparticles.

The one or more contrast agents may be exogenous to the target.Alternatively, the one or more contrast agents may be endogenous to thetarget.

According to another aspect there is provided a method of ambientionisation comprising a method as disclosed above.

According to another aspect there is provided a method of rapidevaporation ionization mass spectrometry (“REIMS”) comprising a methodas disclosed above.

According to another aspect there is provided a method of analysiscomprising a method as disclosed above.

According to another aspect there is provided a method of surgery,diagnosis, therapy or medical treatment comprising a method as disclosedabove.

According to another aspect there is provided a non-surgical,non-therapeutic method of mass spectrometry and/or method of ionmobility spectrometry comprising a method as disclosed above.

According to another aspect there is provided a method of massspectrometry and/or a method of ion mobility spectrometry comprising amethod as disclosed above.

According to another aspect there is provided apparatus comprising:

a device arranged and adapted to obtain chemical or other non-massspectrometric data from one or more regions of a target; and

a first device for generating aerosol, smoke or vapour from one or moreregions of the target.

The apparatus may further comprise a control system arranged and adaptedto use the chemical or other non-mass spectrometric data to determineone or more regions of interest of the target.

The chemical or other non-mass spectrometric data may comprise dataselected from the group consisting of: (i) Raman spectroscopy data; (ii)chemical composition data; (iii) fluorescence data; (iv) absorptiondata; (v) reflectance data; (vi) transmission data; (vii) elasticscattering data; (viii) Fourier Transform Infra-Red Spectroscopy (FTIR)data; and (ix) interferometry data.

The first device may comprise or form part of an ambient ion orionisation source or the first device may generate the aerosol, smoke orvapour for subsequent ionisation by an ambient ion or ionisation sourceor other ionisation source.

The target may comprise native or unmodified target material.

The native or unmodified target material may be unmodified by theaddition of a matrix or reagent.

The first device may be arranged and adapted to generate aerosol, smokeor vapour from one or more regions of the target without the targetrequiring prior preparation.

The first device may comprise an ion source selected from the groupconsisting of: (i) a rapid evaporative ionisation mass spectrometry(“REIMS”) ion source; (ii) a desorption electrospray ionisation (“DESI”)ion source; (iii) a laser desorption ionisation (“LDI”) ion source; (iv)a thermal desorption ion source; (v) a laser diode thermal desorption(“LDTD”) ion source; (vi) a desorption electro-flow focusing (“DEFFI”)ion source; (vii) a dielectric barrier discharge (“DBD”) plasma ionsource; (viii) an Atmospheric Solids Analysis Probe (“ASAP”) ion source;(ix) an ultrasonic assisted spray ionisation ion source; (x) an easyambient sonic-spray ionisation (“EASI”) ion source; (xi) a desorptionatmospheric pressure photoionisation (“DAPPI”) ion source; (xii) apaperspray (“PS”) ion source; (xiii) a jet desorption ionisation(“JeDI”) ion source; (xiv) a touch spray (“TS”) ion source; (xv) anano-DESI ion source; (xvi) a laser ablation electrospray (“LAESI”) ionsource; (xvii) a direct analysis in real time (“DART”) ion source;(xviii) a probe electrospray ionisation (“PESI”) ion source; (xix) asolid-probe assisted electrospray ionisation (“SPA-ESI”) ion source;(xx) a cavitron ultrasonic surgical aspirator (“CUSA”) device; (xxi) afocussed or unfocussed ultrasonic ablation device; (xxii) a microwaveresonance device; and (xxiii) a pulsed plasma RF dissection device.

The first device may be arranged and adapted to generate aerosol, smokeor vapour from one or more regions of the target by contacting thetarget with one or more electrodes.

The one or more electrodes may comprise: (i) a monopolar device, whereinthe method optionally further comprises providing a separate returnelectrode; (ii) a bipolar device; or (iii) a multi phase RF device,wherein the method optionally further comprises providing a separatereturn electrode or electrodes.

The one or more electrodes may comprise a rapid evaporation ionizationmass spectrometry (“REIMS”) device.

The apparatus may further comprise a device arranged and adapted toapply an AC or RF voltage to the one or more electrodes in order togenerate the aerosol, smoke or vapour.

The device for applying the AC or RF voltage to the one or moreelectrodes may be arranged to apply one or more pulses of the AC or RFvoltage to the one or more electrodes.

Application of the AC or RF voltage to the one or more electrodes maycause heat to be dissipated into the target.

The first device may comprise a laser for irradiating the target.

The first device may be arranged and adapted to generate aerosol fromone or more regions of the target by direct evaporation or vaporisationof target material from the target by Joule heating or diathermy.

The first device may be arranged and adapted to direct ultrasonic energyinto the target.

The aerosol may comprise uncharged aqueous droplets optionallycomprising cellular material.

At least 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 95% of the massor matter generated by the first device and which forms the aerosol maybe in the form of droplets.

The first device may be arranged and adapted to generate aerosol whereinthe Sauter mean diameter (“SMD”, d32) of the aerosol may be in a range:(i)<5 μm; (ii) 5-10 μm; (iii) 10-15 μm; (iv) 15-20 μm; (v) 20-25 μm; or(vi) >25 μm.

The aerosol may traverse a flow region with a Reynolds number (Re) inthe range: (i)<2000; (ii) 2000-2500; (iii) 2500-3000; (iv) 3000-3500;(v) 3500-4000; or (vi) >4000.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a Weber number (We) selected from the groupconsisting of: (i)<50; (ii) 50-100; (iii) 100-150; (iv) 150-200; (v)200-250; (vi) 250-300; (vii) 300-350; (viii) 350-400; (ix) 400-450; (x)450-500; (xi) 500-550; (xii) 550-600; (xiii) 600-650; (xiv) 650-700;(xv) 700-750; (xvi) 750-800; (xvii) 800-850; (xviii) 850-900; (xix)900-950; (xx) 950-1000; and (xxi) >1000.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a Stokes number (S_(k)) in the range: (i) 1-5;(ii) 5-10; (iii) 10-15; (iv) 15-20; (v) 20-25; (vi) 25-30; (vii) 30-35;(viii) 35-40; (ix) 40-45; (x) 45-50; and (xi) >50.

Substantially at the point of generating the aerosol, the aerosol maycomprise droplets having a mean axial velocity selected from the groupconsisting of: (i)<20 m/s; (ii) 20-30 m/s; (iii) 30-40 m/s; (iv) 40-50m/s; (v) 50-60 m/s; (vi) 60-70 m/s; (vii) 70-80 m/s; (viii) 80-90 m/s;(ix) 90-100 m/s; (x) 100-110 m/s; (xi) 110-120 m/s; (xii) 120-130 m/s;(xiii) 130-140 m/s; (xiv) 140-150 m/s; and (xv) >150 m/s.

The target may comprise biological tissue, biological matter, abacterial colony or a fungal colony.

The biological tissue may comprise human tissue or non-human animaltissue.

The biological tissue may comprise in vivo biological tissue.

The biological tissue may comprise ex vivo biological tissue.

The biological tissue may comprise in vitro biological tissue.

The biological tissue comprise: (i) adrenal gland tissue, appendixtissue, bladder tissue, bone, bowel tissue, brain tissue, breast tissue,bronchi, coronal tissue, ear tissue, esophagus tissue, eye tissue, gallbladder tissue, genital tissue, heart tissue, hypothalamus tissue,kidney tissue, large intestine tissue, intestinal tissue, larynx tissue,liver tissue, lung tissue, lymph nodes, mouth tissue, nose tissue,pancreatic tissue, parathyroid gland tissue, pituitary gland tissue,prostate tissue, rectal tissue, salivary gland tissue, skeletal muscletissue, skin tissue, small intestine tissue, spinal cord, spleen tissue,stomach tissue, thymus gland tissue, trachea tissue, thyroid tissue,ureter tissue, urethra tissue, soft and connective tissue, peritonealtissue, blood vessel tissue and/or fat tissue; (ii) grade I, grade II,grade Ill or grade IV cancerous tissue; (iii) metastatic canceroustissue; (iv) mixed grade cancerous tissue; (v) a sub-grade canceroustissue; (vi) healthy or normal tissue; or (vii) cancerous or abnormaltissue.

The first device may comprise a point of care (“POC”), diagnostic orsurgical device.

The apparatus may further comprise an ion source for ionising at leastsome of the aerosol, smoke or vapour so as to generate analyte ions.

The apparatus may further comprise a device for directing or aspiratingat least some of the aerosol, smoke or vapour into a vacuum chamber of amass spectrometer and/or ion mobility spectrometer.

The apparatus may further comprise a device for ionising at least somethe aerosol, smoke or vapour within a or the vacuum chamber of the massspectrometer and/or ion mobility spectrometer so as to generate aplurality of analyte ions.

The apparatus may further comprise a device for directing the aerosol,smoke or vapour to impact upon a collision surface located within avacuum chamber of the mass spectrometer and/or ion mobility spectrometerso as to generate a plurality of analyte ions.

The apparatus may further comprise a mass analyser and/or ion mobilityspectrometer for mass analysing and/or ion mobility separating theanalyte ions in order to obtain mass spectrometric data and/or ionmobility data.

The apparatus may further comprise a mass analyser and/or ion mobilityspectrometer for mass analysing and/or ion mobility separating theaerosol, smoke or vapour or ions derived from the aerosol, smoke orvapour in order to obtain mass spectrometric data and/or ion mobilitydata.

The apparatus may further comprise a control system arranged and adaptedto analyse the mass spectrometric data and/or ion mobility data in ordereither: (i) to distinguish between healthy and diseased tissue; (ii) todistinguish between potentially cancerous and non-cancerous tissue;(iii) to distinguish between different types or grades of canceroustissue; (iv) to distinguish between different types or classes of targetmaterial; (v) to determine whether or not one or more desired orundesired substances are present in the target; (vi) to confirm theidentity or authenticity of the target; (vii) to determine whether ornot one or more impurities, illegal substances or undesired substancesare present in the target; (viii) to determine whether a human or animalpatient may be at an increased risk of suffering an adverse outcome;(ix) to make or assist in the making a diagnosis or prognosis; and (x)to inform a surgeon, nurse, medic or robot of a medical, surgical ordiagnostic outcome.

The control system may be arranged and adapted to perform a supervisedor unsupervised multivariate statistical analysis of the massspectrometric data and/or ion mobility data.

The multivariate statistical analysis be may be selected from the groupconsisting of: (i) principal component analysis be (“PCA”); and (ii)linear discriminant analysis (“LDA”).

The apparatus may further comprise a control system arranged and adaptedto analyse a profile of the aerosol, smoke or vapour or a profile ofions derived from the aerosol, smoke or vapour.

The profile may be selected from the group consisting of: (i) alipidomic profile; (ii) a fatty acid profile; (iii) a phospholipidprofile; (iv) a phosphatidic acid (PA) profile; (v) aphosphatidylethanolamine (PE) profile; (vi) a phosphatidylglycerol (PG)profile; (vii) a phosphatidylserines (PS) profile; (viii) aphosphatidylinositol (PI) profile; or (ix) a triglyceride (TG) profile.

The apparatus may further comprise one or more Raman spectroscopysensors, detectors or devices for obtaining the chemical or othernon-mass spectrometric data.

The apparatus may further comprise a control system arranged and adaptedto determine the intensity of Raman scattered light as a function ofwavenumber.

The apparatus may further comprise a control system arranged and adaptedto analyse Raman spectroscopy data in order to determine data relatingto vibrations of molecular bonds present within the target.

The one or more Raman spectroscopy sensors, detectors or devices may bearranged to obtain the chemical or other non-mass spectrometric datawith or without the one or more Raman spectroscopy sensors, detectors ordevices physically contacting the target.

The apparatus may further comprise a control system arranged and adaptedto determine a Raman spectrum or Raman profile of one or more regions ofthe target.

The apparatus may further comprise a control system arranged and adaptedto determine one or more regions of interest of the target bydetermining one or more regions of the target which have a differentRaman spectrum, Raman profile or Raman spectral feature relative tonormal tissue, surrounding tissue, a control sample, a control region,control data or predetermined data.

The apparatus may further comprise a control system arranged and adaptedto determine one or more regions of interest of the target bydetermining whether or not a region of the target may have a higher orlower Raman peak intensity relative to normal tissue, surroundingtissue, a control sample, a control region, control data orpredetermined data.

The apparatus may further comprise a device for directing light orultra-violet radiation on to the target.

The ultra-violet radiation may have a wavelength in a range selectedfrom the group consisting of: (i) 100-150 nm; (ii) 150-200 nm; (iii)200-250 nm; (iv) 250-300 nm; (v) 300-350 nm; and (vi) 350-400 nm.

The apparatus may further comprise a detector for detecting light orelectromagnetic radiation emitted from the target.

The apparatus may further comprise a control system arranged and adaptedto determine a fluorescence or autofluorescence profile or spectrum.

The fluorescence or autofluorescence profile or spectrum may comprise ameasure of the intensity of light or electromagnetic radiation emittedfrom the target as a function of frequency or wavelength.

The apparatus may further comprise a control system arranged and adaptedto compare a fluorescence or autofluorescence profile or spectrumrelating to a region of the target with a fluorescence orautofluorescence profile or spectrum obtained from a control sample, acontrol region, control data or predetermined data in order todetermining one or more regions of interest of the target.

The apparatus may further comprise a device arranged to direct light orinfra-red radiation on to the target.

The light or infra-red radiation may have a wavelength in a rangeselected from the group consisting of: (i) 400-450 nm; (ii) 450-500 nm;(iii) 500-550 nm; (iv) 550-600 nm; (v) 600-650 nm; (vi) 650-700 nm;(vii) 700-750 nm; (viii) 750-800 nm; (ix) 800-850 nm; (x) 850-900 nm;(xi) 900-950 nm; (xii) 950-1000 nm; (xiii) 1000-1100 nm; (xiv) 1100-1200nm; (xv) 1200-1300 nm; (xvi) 1300-1400 nm; (xvii) 1400-1500 nm; (xviii)1500-1600 nm; (xix) 1600-1700 nm; ON 1700-1800 nm; (xxi) 1800-1900 nm;(xxii) 1900-2000 nm; (xxiii) 2000-2100 nm; (xxiv) 2100-2200 nm; (xxv)2200-2300 nm; (xxvi) 2300-2400 nm; (xxvii) 2400-2500 nm; (xxviii)2500-2600 nm; (xxix) 2600-2700 nm; (xxx) 2700-2800 nm; (xxxi) 2800-2900nm; and (xxxii) 2900-3000 nm.

The apparatus may further comprise a device arranged to direct whitelight on to the target.

The apparatus may further comprise a device arranged to detect light orinfra-red radiation reflected by or from the target.

The apparatus may further comprise a control system arranged and adaptedto determine an absorbance, transmission or reflectance profile orspectrum of a region of the target.

The absorbance, transmission or reflectance profile or spectrum maycomprise a measure of the intensity of light absorbed by, transmitted byor reflected by the target as a function of frequency or wavelength.

The apparatus may further comprise a control system arranged and adaptedto compare an absorbance, transmission or reflectance profile orspectrum relating to a region of the target with an absorbance,transmission or reflectance profile or spectrum obtained from a controlsample, a control region, control data or predetermined data in order todetermine one or more regions of interest of the target.

The apparatus may further comprise a device arranged and adapted todirect ultra-violet radiation, light or infra-red radiation on to thetarget.

The ultra-violet radiation, light or infra-red radiation may have awavelength in a range selected from the group consisting of: (i) 300-350nm; (ii) 350-400 nm; (iii) 400-450 nm; (iv) 450-500 nm; (v) 500-500 nm;(vi) 500-550 nm; (vii) 550-600 nm; (viii) 600-650 nm; (ix) 650-700 nm;(x) 700-750 nm; (xi) 750-800 nm; (xii) 800-850 nm; (xiii) 850-900 nm;(xiv) 900-950 nm; (xv) 950-1000 nm; (xvi) 1000-1100 nm; (xvii) 1100-1200nm; (xviii) 1200-1300 nm; (xix) 1300-1400 nm; (xx) 1400-1500 nm; (xxi)1500-1600 nm; (xxii) 1600-1700 nm; (xxiii) 1700-1800 nm; (xxiv)1800-1900 nm; (xxv) 1900-2000 nm; (xxvi) 2000-2100 nm; (xxvii) 2100-2200nm; (xxviii) 2200-2300 nm; (xxix) 2300-2400 nm; (xxx) 2400-2500 nm;(xxxi) 2500-2600 nm; (xxxii) 2600-2700 nm; (xxxiii) 2700-2800 nm;(xxxiv) 2800-2900 nm; and (xxxv) 2900-3000 nm.

The apparatus may further comprise a device arranged to direct whitelight on to the target.

The apparatus may further comprise a detector for detecting ultra-violetradiation, light or infra-red radiation reflected or scattered by thetarget.

The apparatus may further comprise a control system arranged and adaptedto determine a scattered light intensity profile or spectrum of a regionof the target.

The scattered light intensity profile or spectrum may comprise a measureof the intensity of light scattered by the target as a function offrequency or wavelength.

The apparatus may further comprise a control system arranged and adaptedto compare a scattered light intensity profile or spectrum relating to aregion of the target with a scattered light intensity profile orspectrum obtained from a control sample, a control region, control dataor predetermined data.

The apparatus may further comprise a control system arranged and adaptedto use the chemical or other non-mass spectrometric data to determinethe margins or bounds of one or more regions of interest of the target.

The one or more regions of interest may comprise cancerous biologicaltissue or a tumour.

The cancerous biological tissue or the tumour may comprise either: (i)grade I, grade II, grade III or grade IV cancerous tissue; (ii)metastatic cancerous tissue; (iii) mixed grade cancerous tissue; or (iv)a sub-grade cancerous tissue.

The apparatus may further comprise a control system arranged and adaptedto determine from the chemical or other non-mass spectrometric dataeither: (i) one or more physical properties of the target; (ii) one ormore chemical properties of the target; (iii) one or morephysico-chemical properties of the target; or (iv) one or moremechanical properties of the target.

The apparatus may further comprise using one or more contrast agents toenhance the chemical data.

The one or more contrast agents may comprise one or more fluorescentcontrast agents.

The one or more contrast agents may comprise one or more visible dyes.

The one or more contrast agents may comprise one or more radiocontrastagents.

The one or more contrast agents may comprise one or more optical, nearinfrared (“NIR”), fluorescent, autofluorescent or diagnostic contrastagents.

The one or more contrast agents may be selected from the groupconsisting of: (i) indocyanine green (“ICG”) and derivatives orconjugates of indocyanine green including indotricarbocyanine; (ii)diethylthiatricarbocyanine iodide (“DTTCI”) and derivatives orconjugates of diethylthiatricarbocyanine iodide; (iii) rhodamine B andderivatives or conjugates of rhodamine B; (iv) photodynamic therapy(“PDT”) agents including hexylpyropheophorbide (“HPPH”); (v) a cyaninedye including Cy 5.5 dyes; and (vi) bifunctional contrast agents.

The one or more contrast agents may comprise nanoparticles.

The one or more contrast agents may comprise: (i) magnetic orferromagnetic nanoparticles; (ii) gold nanoparticles; (iii) metallicnanoparticles; (iv) functionalised nanoparticles; (v) nanospheres,nanorods, nanostars or nanoshells; (vi) levan nanoparticles; or (vii)copper, zinc, titanium, magnesium, alginate, alloy or silvernanoparticles.

The one or more contrast agents may be exogenous to the target.Alternatively, the one or more contrast agents may be endogenous to thetarget.

According to another aspect there is provided an ambient ionisation ionsource comprising apparatus as disclosed above.

According to another aspect there is provided a rapid evaporationionization mass spectrometry (“REIMS”) ion source comprising apparatusas disclosed above.

According to another aspect there is provided analysis apparatus asdisclosed above.

According to another aspect there is provided a mass spectrometer and/orion mobility spectrometer comprising apparatus as disclosed above.

According to another aspect there is provided a method of rapidevaporative ionisation mass spectrometry (“REIMS”) comprising:

using a Raman spectroscopy probe to sample a site;

generating an aerosol from the site; and

mass analysing and/or ion mobility analysing the aerosol or analyte ionsderived from the aerosol.

The site may comprise a surgical site.

The step of using the Raman spectroscopy probe to sample the site maycomprise using information derived from the probe to determine themargins or bounds of one or more undesired objects at the site.

The one or more undesired objects may comprise cancerous biologicaltissue or a tumour.

The cancerous biological tissue or the tumour may comprise grade I,grade II, grade III or grade IV cancerous tissue.

The step of mass analysing and/or ion mobility analysing the aerosol oranalyte ions derived from the aerosol further may comprisedistinguishing between healthy tissue and non-healthy or canceroustissue.

The step of mass analysing and/or ion mobility analysing the aerosol oranalyte ions derived from the aerosol further may comprisedistinguishing between different types or grades of cancerous tissue.

The method may further comprise localising one or more sampling pointsusing ultrasound.

The method may further comprise using an electrosurgical device tosample the site at one or more sampling points.

The electrosurgical device may comprise a bipolar device.

The method may further comprise applying an AC or RF voltage to theelectrosurgical device in order to remove, resect or sample biologicalmaterial from the site.

According to another aspect there is provided a method of surgerycomprising a method as disclosed above.

The method may comprise a method of brain surgery.

According to another aspect there is provided apparatus for performingrapid evaporative ionisation mass spectrometry (“REIMS”) comprising:

a Raman spectroscopy probe for sampling a site;

a device for generating an aerosol from the site; and

a mass analyser and/or ion mobility analyser for mass analysing and/orion mobility analysing the aerosol or analyte ions derived from theaerosol.

According to another aspect there is provided a method of analysing asample comprising:

using a Raman spectroscopy probe to sample a site;

generating an aerosol from the site; and

mass analysing and/or ion mobility analysing the aerosol or analyte ionsderived from the aerosol.

The step of generating an aerosol further may comprise using a laser togenerate the aerosol.

The step of generating an aerosol may further comprise contacting thesite with one or more electrodes and applying an AC or RF voltage to theone or more electrodes.

According to another aspect there is provided apparatus for analysing asample comprising:

a Raman spectroscopy probe for sampling a site;

a device for generating an aerosol from the site; and

a mass analyser and/or ion mobility analyser for mass analysing and/orion mobility analysing the aerosol or analyte ions derived from theaerosol.

According to another aspect there is provided a method of biologicaltissue typing comprising:

contacting a portion of tissue with one or more electrodes;

applying an AC or RF voltage to the one or more electrodes in order togenerate an aerosol from the portion of tissue;

mass analysing and/or ion mobility analysing the aerosol or analyte ionsderived from the aerosol in order to generate mass spectral data and/orion mobility data; and

analysing the mass spectral data and/or ion mobility data in order todistinguish between different types of tissue.

The different types of tissue may comprise different grades, forms ortypes of cancerous biological tissue or tumours.

The step of analysing the mass spectral data in order to distinguishbetween different types of tissue further may comprise distinguishingbetween grade I and/or grade II and/or grade III and/or grade IVcancerous tissue.

According to another aspect there is provided apparatus for biologicaltissue typing comprising:

one or more electrodes which may be arranged and adapted to contact aportion of tissue;

a device for applying an AC or RF voltage to the one or more electrodesin order to generate an aerosol from the portion of tissue;

a mass analyser and/or ion mobility analyser for mass analysing and/orion mobility analysing the aerosol or analyte ions derived from theaerosol in order to generate mass spectral data; and

a control system for analysing the mass spectral data and/or ionmobility data in order to distinguish between different types of tissue.

Various embodiments are contemplated which relate to generating smoke,aerosol or vapour from a target (details of which are provided elsewhereherein) using an ambient ionisation ion source. The aerosol, smoke orvapour may then be mixed with a matrix and aspirated into a vacuumchamber of a mass spectrometer and/or ion mobility spectrometer. Themixture may be caused to impact upon a collision surface causing theaerosol, smoke or vapour to be ionised by impact ionization whichresults in the generation of analyte ions. The resulting analyte ions(or fragment or product ions derived from the analyte ions) may then bemass analysed and/or ion mobility analysed and the resulting massspectrometric data and/or ion mobility spectrometric data may besubjected to multivariate analysis or other mathematical treatment inorder to determine one or more properties of the target in real time.

According to an embodiment the first device for generating aerosol,smoke or vapour from the target may comprise a tool which utilises an RFvoltage, such as a continuous RF waveform.

Other embodiments are contemplated wherein the first device forgenerating aerosol, smoke or vapour from the target may comprise anargon plasma coagulation (“APC”) device. An argon plasma coagulationdevice involves the use of a jet of ionised argon gas (plasma) that isdirected through a probe. The probe may be passed through an endoscope.Argon plasma coagulation is essentially a non-contact process as theprobe is placed at some distance from the target. Argon gas is emittedfrom the probe and is then ionized by a high voltage discharge (e.g., 6kV). High-frequency electric current is then conducted through the jetof gas, resulting in coagulation of the target on the other end of thejet. The depth of coagulation is usually only a few millimetres.

The first device, surgical or electrosurgical tool, device or probe orother sampling device or probe disclosed in any of the aspects orembodiments herein may comprise a non-contact surgical device, such asone or more of a hydrosurgical device, a surgical water jet device, anargon plasma coagulation device, a hybrid argon plasma coagulationdevice, a water jet device and a laser device.

A non-contact surgical device may be defined as a surgical devicearranged and adapted to dissect, fragment, liquefy, aspirate, fulgurateor otherwise disrupt biologic tissue without physically contacting thetissue. Examples include laser devices, hydrosurgical devices, argonplasma coagulation devices and hybrid argon plasma coagulation devices.

As the non-contact device may not make physical contact with the tissue,the procedure may be seen as relatively safe and can be used to treatdelicate tissue having low intracellular bonds, such as skin or fat.

According to various embodiments the mass spectrometer and/or ionmobility spectrometer may obtain data in negative ion mode only,positive ion mode only, or in both positive and negative ion modes.Positive ion mode spectrometric data may be combined or concatenatedwith negative ion mode spectrometric data. Negative ion mode can provideparticularly useful spectra for classifying aerosol, smoke or vapoursamples, such as aerosol, smoke or vapour samples from targetscomprising lipids.

Ion mobility spectrometric data may be obtained using different ionmobility drift gases, or dopants may be added to the drift gas to inducea change in drift time of one or more species. This data may then becombined or concatenated.

It will be apparent that the requirement to add a matrix or a reagentdirectly to a sample may prevent the ability to perform in vivo analysisof tissue and also, more generally, prevents the ability to provide arapid simple analysis of target material.

According to other embodiments the ambient ionisation ion source maycomprise an ultrasonic ablation ion source or a hybridelectrosurgical—ultrasonic ablation source that generates a liquidsample which is then aspirated as an aerosol. The ultrasonic ablationion source may comprise a focused or unfocussed ultrasound.

Optionally, the first device comprises or forms part of an ion sourceselected from the group consisting of: (i) a rapid evaporativeionisation mass spectrometry (“REIMS”) ion source; (ii) a desorptionelectrospray ionisation (“DESI”) ion source; (iii) a laser desorptionionisation (“LDI”) ion source; (iv) a thermal desorption ion source; (v)a laser diode thermal desorption (“LDTD”) ion source; (vi) a desorptionelectro-flow focusing (“DEFFI”) ion source; (vii) a dielectric barrierdischarge (“DBD”) plasma ion source; (viii) an Atmospheric SolidsAnalysis Probe (“ASAP”) ion source; (ix) an ultrasonic assisted sprayionisation ion source; (x) an easy ambient sonic-spray ionisation(“EASI”) ion source; (xi) a desorption atmospheric pressurephotoionisation (“DAPPI”) ion source; (xii) a paperspray (“PS”) ionsource; (xiii) a jet desorption ionisation (“JeDI”) ion source; (xiv) atouch spray (“TS”) ion source; (xv) a nano-DESI ion source; (xvi) alaser ablation electrospray (“LAESI”) ion source; (xvii) a directanalysis in real time (“DART”) ion source; (xviii) a probe electrosprayionisation (“PESI”) ion source; (xix) a solid-probe assistedelectrospray ionisation (“SPA-ESI”) ion source; (xx) a cavitronultrasonic surgical aspirator (“CUSA”) device; (xxi) a hybridCUSA-diathermy device; (xxii) a focussed or unfocussed ultrasonicablation device; (xxiii) a hybrid focussed or unfocussed ultrasonicablation and diathermy device; (xxiv) a microwave resonance device;(xxv) a pulsed plasma RF dissection device; (xxvi) an argon plasmacoagulation device; (xxvi) a hybrid pulsed plasma RF dissection andargon plasma coagulation device; (xxvii) a hybrid pulsed plasma RFdissection and JeDI device; (xxviii) a surgical water/saline jet device;(xxix) a hybrid electrosurgery and argon plasma coagulation device; and(xxx) a hybrid argon plasma coagulation and water/saline jet device.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments will now be described, by way of example only, andwith reference to the accompanying drawings in which:

FIG. 1 illustrates a method of rapid evaporative ionisation massspectrometry (“REIMS”) wherein an RF voltage is applied to bipolarforceps resulting in the generation of an aerosol or surgical plumewhich is then captured through an irrigation port of the bipolar forcepsand is then transferred to a mass spectrometer for mass analysis;

FIG. 2 illustrates a general embodiment wherein one or more chemicalsensors are used to obtain chemical data from a target (e.g. in vivotissue) prior to activating a rapid evaporative ionisation massspectrometry (“REIMS”) ion source to inter alia analyse the target andto determine, for example, whether or not the tissue is cancerous;

FIG. 3 shows a method of analysis that comprises building aclassification model according to various embodiments;

FIG. 4 shows a set of reference sample spectra obtained from two classesof known reference samples;

FIG. 5 shows a multivariate space having three dimensions defined byintensity axes, wherein the multivariate space comprises pluralreference points, each reference point corresponding to a set of threepeak intensity values derived from a reference sample spectrum;

FIG. 6 shows a general relationship between cumulative variance andnumber of components of a PCA model;

FIG. 7 shows a PCA space having two dimensions defined by principalcomponent axes, wherein the PCA space comprises plural transformedreference points or scores, each transformed reference point or scorecorresponding to a reference point of FIG. 5;

FIG. 8 shows a PCA-LDA space having a single dimension or axis, whereinthe LDA is performed based on the PCA space of FIG. 7, the PCA-LDA spacecomprising plural further transformed reference points or class scores,each further transformed reference point or class score corresponding toa transformed reference point or score of FIG. 7;

FIG. 9 shows a method of analysis that comprises using a classificationmodel according to various embodiments;

FIG. 10 shows a sample spectrum obtained from an unknown sample;

FIG. 11 shows the PCA-LDA space of FIG. 8, wherein the PCA-LDA spacefurther comprises a PCA-LDA projected sample point derived from the peakintensity values of the sample spectrum of FIG. 10;

FIG. 12 shows a method of analysis that comprises building aclassification library according to various embodiments;

FIG. 13 shows a method of analysis that comprises using a classificationlibrary according to various embodiments;

FIG. 14 shows a Raman sampling system according to an embodiment;

FIG. 15 shows illustrates an embodiment wherein various sampling pointsduring brain surgery were subjected to Raman sampling and wherein thesampling points were then localised using a 3D in vivo ultrasonic systemand rapid evaporative ionisation mass spectrometry (“REIMS”) samplingwas then performed at the same sampling points;

FIG. 16 shows on the left-hand side a case study of a patient sufferingfrom Glioblastoma multiforme (“GBM”) and shows a 3D image of thepatient's brain which is overlayed by real time ultrasonic image andwherein an aerosol was generated by rapid evaporative ionisation massspectrometry (“REIMS”) from six sampling points (which are shown on theimage) during surgery, wherein corresponding mass spectra which wererecorded at each sampling point are shown (right bottom) together with a3D PCA plot of all sampling point taken during the surgery and aslabelled by a neuropathologist;

FIG. 17 shows a 3D pseudo LDA plot of ten patients who were sufferingfrom four different tumour types and shows that high and low gradetumours separate well on the space although some grade IIIoligodendroglioma tumours group with low grade tumours;

FIG. 18 shows (above) mass spectra obtained by rapid evaporativeionisation mass spectrometry (“REIMS”) together with a 3D PCA plot(below) from two sampling points, one consisting mainly from tumour, theother mainly from normal white matter and wherein there is a visibledifference in the phospholipid composition (a trend can be observed fromright to left on the PCA plot showing the amount of infiltration withinthe normal brain cells); and

FIG. 19 shows Raman spectra (above) and a 3D PCA plot (below) from thesame sampling points, one consisting mainly from the tumour, the otherfrom normal white matter wherein the main differences observed on thePCA plot are due to the lipid vibration region.

DETAILED DESCRIPTION

Various embodiments will now be described in more detail below which ingeneral relate to obtaining chemical or other non-mass spectrometricdata from one or more regions of a target (e.g., in vivo tissue) andthen generating an aerosol, surgical smoke or vapour from one or moreregions of the target using an ambient ionisation ion source.

The aerosol, surgical smoke or vapour is then aspirated into a vacuumchamber of a mass spectrometer and is caused to impact upon a collisionsurface causing the aerosol, smoke or vapour to be ionised by impactionisation which results in the generation of analyte ions.

The resulting analyte ions (or fragment or product ions derived from theanalyte ions) are then mass analysed and the resulting massspectrometric data and/or ion mobility data may then be subjected tomultivariate analysis in order to determine one or more properties ofthe target in real time.

For example, the multivariate analysis may enable a determination to bemade as to whether or not a portion of tissue which is currently beingresected is cancerous or not.

The use of chemical data enables tissue which is of potential concern tobe identified either prior to and/or during a surgical procedure andenables a surgeon to have a greater confidence that all undesired orpotentially cancerous tissue is both located and completely removedwhilst at the same time ensuring that the minimum amount of healthytissue is removed.

Ambient Ionisation Ion Sources

According to various embodiments a device is used to generate anaerosol, smoke or vapour from one or more regions of a target (e.g., invivo tissue). The device may comprise an ambient ionisation ion sourcewhich is characterised by the ability to generate analyte aerosol, smokeor vapour from a native or unmodified target. For example, other typesof ionisation ion sources such as Matrix Assisted Laser DesorptionIonisation (“MALDI”) ion sources require a matrix or reagent to be addedto the sample prior to ionisation.

It will be apparent that the requirement to add a matrix or a reagent toa sample prevents the ability to perform in vivo analysis of tissue andalso, more generally, prevents the ability to provide a rapid simpleanalysis of target material.

In contrast, therefore, ambient ionisation techniques are particularlyadvantageous since firstly they do not require the addition of a matrixor a reagent (and hence are suitable for the analysis of in vivo tissue)and since secondly they enable a rapid simple analysis of targetmaterial to be performed.

A number of different ambient ionisation techniques are known and areintended to fall within the scope of the present invention. As a matterof historical record, Desorption Electrospray Ionisation (“DESI”) wasthe first ambient ionisation technique to be developed and was disclosedin 2004. Since 2004, a number of other ambient ionisation techniqueshave been developed. These ambient ionisation techniques differ in theirprecise ionisation method but they share the same general capability ofgenerating gas-phase ions directly from native (i.e. untreated orunmodified) samples. A particular advantage of the various ambientionisation techniques which are intended to fall within the scope of thepresent invention is that the various ambient ionisation techniques donot require any prior sample preparation. As a result, the variousambient ionisation techniques enable both in vivo tissue and ex vivotissue samples to be analysed without necessitating the time and expenseof adding a matrix or reagent to the tissue sample or other targetmaterial.

A list of ambient ionisation techniques which are intended to fallwithin the scope of the present invention are given in the followingtable:

Acronym Ionisation technique DESI Desorption electrospray ionizationDeSSI Desorption sonic spray ionization DAPPI Desorption atmosphericpressure photoionization EASI Easy ambient sonic-spray ionization JeDIJet desorption electrospray ionization TM-DESI Transmission modedesorption electrospray ionization LMJ-SSP Liquid microjunction-surfacesampling probe DICE Desorption ionization by charge exchange Nano-DESINanospray desorption electrospray ionization EADESI Electrode-assisteddesorption electrospray ionization APTDCI Atmospheric pressure thermaldesorption chemical ionization V-EASI Venturi easy ambient sonic-sprayionization AFAI Air flow-assisted ionization LESA Liquid extractionsurface analysis PTC-ESI Pipette tip column electrospray ionizationAFADESI Air flow-assisted desorption electrospray ionization DEFFIDesorption electro-flow focusing ionization ESTASI Electrostatic sprayionization PASIT Plasma-based ambient sampling ionization transmissionDAPCI Desorption atmospheric pressure chemical ionization DART Directanalysis in real time ASAP Atmospheric pressure solid analysis probeAPTDI Atmospheric pressure thermal desorption ionization PADI Plasmaassisted desorption ionization DBDI Dielectric barrier dischargeionization FAPA Flowing atmospheric pressure afterglow HAPGDI Heliumatmospheric pressure glow discharge ionization APGDDI Atmosphericpressure glow discharge desorption ionization LTP Low temperature plasmaLS-APGD Liquid sampling-atmospheric pressure glow discharge MIPDIMicrowave induced plasma desorption ionization MFGDP Microfabricatedglow discharge plasma RoPPI Robotic plasma probe ionization PLASI Plasmaspray ionization MALDESI Matrix assisted laser desorption electrosprayionization ELDI Electrospray laser desorption ionization LDTD Laserdiode thermal desorption LAESI Laser ablation electrospray ionizationCALDI Charge assisted laser desorption ionization LA-FAPA Laser ablationflowing atmospheric pressure afterglow LADESI Laser assisted desorptionelectrospray ionization LDESI Laser desorption electrospray ionizationLEMS Laser electrospray mass spectrometry LSI Laser spray ionizationIR-LAMICI Infrared laser ablation metastable induced chemical ionizationLDSPI Laser desorption spray post-ionization Plasma assistedmultiwavelength laser PAMLDI desorption ionization High voltage-assistedlaser desorption HALDI ionization PALDI Plasma assisted laser desorptionionization ESSI Extractive electrospray ionization PESI Probeelectrospray ionization ND-ESSI Neutral desorption extractiveelectrospray ionization PS Paper spray DIP-APCI Direct inletprobe-atmospheric pressure chemical ionization TS Touch spray Wooden-tipWooden-tip electrospray CBS-SPME Coated blade spray solid phasemicroextraction TSI Tissue spray ionization RADIO Radiofrequencyacoustic desorption ionization LIAD-ESI Laser induced acousticdesorption electrospray ionization SAWN Surface acoustic wavenebulization UASI Ultrasonication-assisted spray ionization SPA-nanoESISolid probe assisted nanoelectrospray ionization PAUSI Paper assistedultrasonic spray ionization DPESI Direct probe electrospray ionizationESA-Py Electrospray assisted pyrolysis ionization APPIS Ambient pressurepyroelectric ion source RASTIR Remote analyte sampling transport andionization relay SACI Surface activated chemical ionization DEMIDesorption electrospray metastable-induced ionization REIMS Rapidevaporative ionization mass spectrometry SPAM Single particle aerosolmass spectrometry TDAMS Thermal desorption-based ambient massspectrometry MAII Matrix assisted inlet ionization SAII Solvent assistedinlet ionization SwiFERR Switched ferroelectric plasma ionizer LPTDLeidenfrost phenomenon assisted thermal desorption

According to an embodiment the ambient ionisation ion source maycomprise a rapid evaporative ionisation mass spectrometry (“REIMS”) ionsource wherein a RF voltage is applied to one or more electrodes inorder to generate an aerosol or plume of surgical smoke by Jouleheating.

However, it will be appreciated that other ambient ion sources includingthose referred to above may also be utilised. For example, according toanother embodiment the ambient ionisation ion source may comprise alaser ionisation ion source. According to an embodiment the laserionisation ion source may comprise a mid-IR laser ablation ion source.For example, there are several lasers which emit radiation close to orat 2.94 μm which corresponds with the peak in the water absorptionspectrum. According to various embodiments the ambient ionisation ionsource may comprise a laser ablation ion source having a wavelengthclose to 2.94 μm on the basis of the high absorption coefficient ofwater at 2.94 μm. According to an embodiment the laser ablation ionsource may comprise a Er:YAG laser which emits radiation at 2.94 μm.

Other embodiments are contemplated wherein a mid-infrared opticalparametric oscillator (“OPO”) may be used to produce a laser ablationion source having a longer wavelength than 2.94 μm. For example, anEr:YAG pumped ZGP-OPO may be used to produce laser radiation having awavelength of e.g. 6.1 μm, 6.45 μm or 6.73 μm. In some situations it maybe advantageous to use a laser ablation ion source having a shorter orlonger wavelength than 2.94 μm since only the surface layers will beablated and less thermal damage may result. According to an embodiment aCo:MgF₂ laser may be used as a laser ablation ion source wherein thelaser may be tuned from 1.75-2.5 μm. According to another embodiment anoptical parametric oscillator (“OPO”) system pumped by a Nd:YAG lasermay be used to produce a laser ablation ion source having a wavelengthbetween 2.9-3.1 μm. According to another embodiment a CO₂ laser having awavelength of 10.6 μm may be used to generate the aerosol, smoke orvapour.

According to other embodiments the ambient ionisation ion source maycomprise an ultrasonic ablation ion source which generates a liquidsample which is then aspirated as an aerosol. The ultrasonic ablationion source may comprise a focused or unfocussed source.

According to an embodiment the first device for generating aerosol,smoke or vapour from one or more regions of a target may comprise anelectrosurgical tool which utilises a continuous RF waveform. Accordingto other embodiments a radiofrequency tissue dissection system may beused which is arranged to supply pulsed plasma RF energy to a tool. Thetool may comprise, for example, a PlasmaBlade®. Pulsed plasma RF toolsoperate at lower temperatures than conventional electrosurgical tools(e.g. 40-170° C. c.f. 200-350° C.) thereby reducing thermal injurydepth. Pulsed waveforms and duty cycles may be used for both cut andcoagulation modes of operation by inducing electrical plasma along thecutting edge(s) of a thin insulated electrode.

Rapid Evaporative Ionisation Mass Spectrometry (“REIMS”)

FIG. 1 illustrates a method of rapid evaporative ionisation massspectrometry (“REIMS”) wherein bipolar forceps 1 may be brought intocontact with in vivo tissue 2 of a patient 3. In the example shown inFIG. 1, the bipolar forceps 1 may be brought into contact with braintissue 2 of a patient 3 during the course of a surgical operation on thepatient's brain. An RF voltage from an RF voltage generator 4 may beapplied to the bipolar forceps 1 which causes localised Joule ordiathermy heating of the tissue 2. As a result, an aerosol or surgicalplume 5 is generated. The aerosol or surgical plume 5 may then becaptured or otherwise aspirated through an irrigation port of thebipolar forceps 1. The irrigation port of the bipolar forceps 1 istherefore reutilised as an aspiration port. The aerosol or surgicalplume 5 may then be passed from the irrigation (aspiration) port of thebipolar forceps 1 to tubing 6 (e.g. ⅛″ or 3.2 mm diameter Teflon®tubing). The tubing 6 is arranged to transfer the aerosol or surgicalplume 5 to an atmospheric pressure interface 7 of a mass spectrometer 8and/or ion mobility analyser.

According to various embodiments a matrix comprising an organic solventsuch as isopropanol may be added to the aerosol or surgical plume 5 atthe atmospheric pressure interface 7. The mixture of aerosol 3 andorganic solvent may then be arranged to impact upon a collision surfacewithin a vacuum chamber of the mass spectrometer and/or ion mobilityanalyser 8. According to one embodiment the collision surface may beheated. The aerosol is caused to ionise upon impacting the collisionsurface resulting in the generation of analyte ions. The ionisationefficiency of generating the analyte ions may be improved by theaddition of the organic solvent. However, the addition of an organicsolvent is not essential.

Analyte ions which are generated by causing the aerosol, smoke or vapour5 to impact upon the collision surface are then passed throughsubsequent stages of the mass spectrometer (and/or ion mobilityanalyser) and are subjected to mass analysis in a mass analyser (and/orion mobility analysis). The mass analyser may, for example, comprise aquadrupole mass analyser or a Time of Flight mass analyser.

FIG. 2 illustrates a general embodiment wherein one or more chemicalsensors 20 are used to obtain chemical data from a target 2 (e.g. invivo tissue) prior to activating a rapid evaporative ionisation massspectrometry (“REIMS”) ion source 1 which inter alia samples tissue 2and enables a determination to be made, for example, as to whether ornot the issue is cancerous.

According to various embodiments the one or more sensor devices 20 maybe used to obtain chemical (or other closely related) non-massspectrometric data from the target (e.g. either in vivo or ex vivobiological tissue). The one or more chemical sensor devices 20 may bearranged, for example, to obtain from the target: (i) Raman spectroscopydata; (ii) chemical composition data; (iii) fluorescence data; (iv)absorption data; (v) reflectance data; (vi) transmission data; (vii)elastic scattering data; (viii) Fourier Transform Infra-Red Spectroscopy(FTIR) data; and (ix) interferometry data.

A number of different embodiments are contemplated and will be describedin more detail below wherein chemical (or other closely related) data isacquired using one or more chemical sensors or devices 20 and whereinthe chemical data may then be used, for example, to guide a user (e.g. asurgeon) performing a surgical, diagnostic or other procedure utilisingan ambient ionisation ion source to one or more regions of particularinterest on a target (e.g. in vivo or ex vivo tissue).

By way of example only, the one or more chemical sensors or devices 20may be utilised to determine regions of tissue of a patient which have adifferent Raman spectroscopy, chemical composition, fluorescence,absorption, reflectance, transmission or elastic scattering profilecompared to surrounding tissue. As will be appreciated, portions oftissue which have a different Raman spectroscopy, chemical composition,fluorescence, absorption, reflectance, transmission or elasticscattering profile compared to surrounding tissue may comprise diseasedor potentially cancerous tissue. It is known, for example, thatpotentially cancerous tissue may be denser than healthy tissue and mayhave a highly vascular nature. Accordingly, potentially cancerous tissuemay have a different water content to that of surrounding healthytissue, may have a higher or different temperature to that of healthytissue and have different chemical properties to that of surroundinghealthy tissue.

According to an embodiment the additional or confirmatory informationprovided by the one or more chemical sensors 20 may be used to helpdetermine the margins or bounds of healthy, potentially cancerous,cancerous, potentially diseased or diseased biological tissue or themargins or bounds of a tumour.

The cancerous biological tissue or the tumour may comprise grade I,grade II, grade III or grade IV cancerous tissue.

The one or more chemical sensors 20 may be used to help determinephysical, chemical or other non-mass spectrometric data and inparticular may be used to determine the margins or bounds betweendifferent types or grades of diseased or cancerous tissue.

The different grades of cancerous tissue may be selected from the groupconsisting of: (i) grade I cancerous tissue; (ii) grade II canceroustissue; (iii) grade III cancerous tissue; and (iv) grade IV canceroustissue.

According to various embodiments a determination from the chemical orother non-mass spectrometric data may be made to determine either: (i)one or more physical properties of the target; (ii) one or more chemicalproperties of the target; (iii) one or more physico-chemical propertiesof the target; or (iv) one or more mechanical properties of the target.

Optimised Operational Parameters of an Ambient Ionisation Surgical orDiagnostic Tool May be Programmed or Set Dependent Upon Data Acquiredfrom One or More Chemical Sensors

According to an embodiment one or more operational parameters of anambient ionisation surgical or diagnostic tool may be arranged to varyor otherwise be optimised during a surgical or diagnostic procedurebased upon the acquired chemical data.

For example, according to an embodiment the energy dissipated intosurrounding tissue may be arranged to reduce as the surgical ordiagnostic device approaches a vital organ.

According to various embodiments one more operational parameters of anambient ionisation ion source may be varied or controlled depending uponthe specific type of tissue which is being probed. The type of tissuemay be known in advance or may be determined from imaging, chemical,physical or other data. For example, according to an embodiment if atissue or tumour has a soft or gelatinous texture or the probe is inclose proximity to a sensitive region of the body (e.g. the probe is inclose proximity to important nerves) than the power and/or duty cycle ofthe ambient ionisation ion source may be reduced, varied or otherwisealtered.

According to another embodiment, one or more operational parameters ofan ambient ionisation surgical or other tool may be set based upon theacquired chemical data. For example, one or more operational parametersof an ambient ionisation surgical tool may be set based upon the type orgrade of cancerous tissue identified by the one or more chemical sensorsor devices 20 or based upon the nature of the diseased tissue identifiedby the one or more chemical sensors or devices 20.

Different operational parameters may be used depending upon whetheroperating upon healthy tissue, clearly cancerous tissue or at the cancermargin.

According to various embodiments the chemical or other non-massspectrometric data may include spatial information and hence thevariation of tissue as a function of depth within an organ may bedetermined. Accordingly, previously acquired chemical data may be usedto set various operational parameters of an ambient ionisation surgicaltool as the surgical tool moves deeper into (or out of) an organ orcloser to (or away from) an organ or specific tissue types.

Furthermore, various ionisation parameters may be varied as the ambientionisation surgical tool moves deeper into (or out of) an organ orcloser to (or away from) an organ or specific tissue types.

As the ambient ionisation surgical tool makes an initial cut into anorgan one or more ionisation parameters (e.g. the composition of amatrix added to the aerosol, smoke or vapour released from the tissue,the temperature of a ionisation collision surface, the voltage appliedto an ionisation collision surface etc.) may be optimised for thesurgical conditions (e.g. initial blood loss, tissue composition)experienced when cutting into the organ. As the ambient ionisationsurgical tool moves deeper into (or out of) the organ or closer to (oraway from) an organ or specific tissue types the optimum ionisationparameters for the surgical tool may change reflecting e.g. a differentdegree of blood loss and a different composition of the tissue.Accordingly, one or more ionisation parameters (e.g. the composition ofmatrix added to aerosol, smoke or vapour released from the tissue, thetemperature of a ionisation collision surface, the voltage applied to anionisation collision surface etc.) may be arranged also to change orvary in order to match the changing surgical conditions and optionallybased upon the acquired chemical data.

Numerous different embodiments are contemplated wherein variousoperational parameters of a surgical device or diagnostic tool whichincorporates an ambient ionisation ion source (e.g. a rapid evaporativeionisation mass spectrometry (“REIMS”) ion source) may be varied basedupon the acquired chemical data.

According to various embodiments an ion mode of the mass spectrometermay be selected based upon chemical, physical, imaging or other datataken or determined from the cutting site.

According to further embodiments one or more operational parameters ofthe mass spectrometer may be changed or altered based upon, subsequentto or during the process of making a diagnosis (e.g. of cancerous orhealthy tissue). For example, one or more operational parameters may bechanged upon confirmation. The one or more operational parameters whichmay be changed or optimised depending upon the stage of analysis (e.g.exploratory, diagnosis or confirmation) include optimisation of: (i)inlet conditions including inlet voltages, type and flow rate ofoptional matrix added to aerosol flow, Venturi suction etc.; (ii)fragmentation conditions for aerosol including flow rates andtemperature of collision surface, heated coil parameters etc.; (iii)downstream ion optics including ion path; and (iv) mass analysis stepsincluding selection of mass peak(s) for further diagnosis, performingMS/MS experiments, fragmenting analyte ions of interest and massanalysing subsequent daughter, fragment or product ions.

Multivariate Analysis—Developing a Model for Classification

By way of example, a method of building a classification model usingmultivariate analysis of plural reference sample spectra will now bedescribed.

FIG. 3 shows a method 1500 of building a classification model usingmultivariate analysis. In this example, the method comprises a step 1502of obtaining plural sets of intensity values for reference samplespectra. The method then comprises a step 1504 of unsupervised principalcomponent analysis (PCA) followed by a step 1506 of supervised lineardiscriminant analysis (LDA). This approach may be referred to herein asPCA-LDA. Other multivariate analysis approaches may be used, such asPCA-MMC. The PCA-LDA model is then output, for example to storage, instep 1508.

The multivariate analysis such as this can provide a classificationmodel that allows an aerosol, smoke or vapour sample to be classifiedusing one or more sample spectra obtained from the aerosol, smoke orvapour sample. The multivariate analysis will now be described in moredetail with reference to a simple example.

FIG. 4 shows a set of reference sample spectra obtained from two classesof known reference samples. The classes may be any one or more of theclasses of target described herein. However, for simplicity, in thisexample the two classes will be referred as a left-hand class and aright-hand class.

Each of the reference sample spectra has been pre-processed in order toderive a set of three reference peak-intensity values for respectivemass to charge ratios in that reference sample spectrum. Although onlythree reference peak-intensity values are shown, it will be appreciatedthat many more reference peak-intensity values (e.g., ˜100 referencepeak-intensity values) may be derived for a corresponding number of massto charge ratios in each of the reference sample spectra. In otherembodiments, the reference peak-intensity values may correspond to:masses; mass to charge ratios; ion mobilities (drift times); and/oroperational parameters.

FIG. 5 shows a multivariate space having three dimensions defined byintensity axes. Each of the dimensions or intensity axes corresponds tothe peak-intensity at a particular mass to charge ratio. Again, it willbe appreciated that there may be many more dimensions or intensity axes(e.g., ˜100 dimensions or intensity axes) in the multivariate space. Themultivariate space comprises plural reference points, with eachreference point corresponding to a reference sample spectrum, i.e., thepeak-intensity values of each reference sample spectrum provide theco-ordinates for the reference points in the multivariate space.

The set of reference sample spectra may be represented by a referencematrix D having rows associated with respective reference samplespectra, columns associated with respective mass to charge ratios, andthe elements of the matrix being the peak-intensity values for therespective mass to charge ratios of the respective reference samplespectra.

In many cases, the large number of dimensions in the multivariate spaceand matrix D can make it difficult to group the reference sample spectrainto classes. PCA may accordingly be carried out on the matrix D inorder to calculate a PCA model that defines a PCA space having a reducednumber of one or more dimensions defined by principal component axes.The principal components may be selected to be those that comprise or“explain” the largest variance in the matrix D and that cumulativelyexplain a threshold amount of the variance in the matrix D.

FIG. 6 shows how the cumulative variance may increase as a function ofthe number n of principal components in the PCA model. The thresholdamount of the variance may be selected as desired.

The PCA model may be calculated from the matrix D using a non-lineariterative partial least squares (NIPALS) algorithm or singular valuedecomposition, the details of which are known to the skilled person andso will not be described herein in detail. Other methods of calculatingthe PCA model may be used.

The resultant PCA model may be defined by a PCA scores matrix S and aPCA loadings matrix L. The PCA may also produce an error matrix E, whichcontains the variance not explained by the PCA model. The relationshipbetween D, S, L and E may be:

D=SL ^(T) +E  (1)

FIG. 7 shows the resultant PCA space for the reference sample spectra ofFIGS. 4 and 5. In this example, the PCA model has two principalcomponents PC₀ and PC₁ and the PCA space therefore has two dimensionsdefined by two principal component axes. However, a lesser or greaternumber of principal components may be included in the PCA model asdesired. It is generally desired that the number of principal componentsis at least one less than the number of dimensions in the multivariatespace.

The PCA space comprises plural transformed reference points or PCAscores, with each transformed reference point or PCA score correspondingto a reference sample spectrum of FIG. 4 and therefore to a referencepoint of FIG. 5.

As is shown in FIG. 7, the reduced dimensionality of the PCA space makesit easier to group the reference sample spectra into the two classes.Any outliers may also be identified and removed from the classificationmodel at this stage.

Further supervised multivariate analysis, such as multi-class LDA ormaximum margin criteria (MMC), in the PCA space may then be performed soas to define classes and, optionally, further reduce the dimensionality.

As will be appreciated by the skilled person, multi-class LDA seeks tomaximise the ratio of the variance between classes to the variancewithin classes (i.e., so as to give the largest possible distancebetween the most compact classes possible). The details of LDA are knownto the skilled person and so will not be described herein in detail.

The resultant PCA-LDA model may be defined by a transformation matrix U,which may be derived from the PCA scores matrix S and class assignmentsfor each of the transformed spectra contained therein by solving ageneralised eigenvalue problem.

The transformation of the scores S from the original PCA space into thenew LDA space may then be given by:

Z=SU  (2)

wherein the matrix Z contains the scores transformed into the LDA space.

FIG. 8 shows a PCA-LDA space having a single dimension or axis, whereinthe LDA is performed in the PCA space of FIG. 7. As is shown in FIG. 8,the LDA space comprises plural further transformed reference points orPCA-LDA scores, with each further transformed reference pointcorresponding to a transformed reference point or PCA score of FIG. 7.

In this example, the further reduced dimensionality of the PCA-LDA spacemakes it even easier to group the reference sample spectra into the twoclasses. Each class in the PCA-LDA model may be defined by itstransformed class average and covariance matrix or one or morehyperplanes (including points, lines, planes or higher orderhyperplanes) or hypersurfaces or Voronoi cells in the PCA-LDA space.

The PCA loadings matrix L, the LDA matrix U and transformed classaverages and covariance matrices or hyperplanes or hypersurfaces orVoronoi cells may be output to a database for later use in classifyingan aerosol, smoke or vapour sample.

The transformed covariance matrix in the LDA space V′_(g) for class gmay be given by:

V′ _(g) =U ^(T) V _(g) U  (3)

wherein V_(g) are the class covariance matrices in the PCA space.

The transformed class average position z_(g) for class g may be givenby:

s _(g) U=z _(g)  (4)

wherein s_(g) is the class average position in the PCA space.

Multivariate Analysis—Using a Model for Classification

By way of example, a method of using a classification model to classifyan aerosol, smoke or vapour sample will now be described.

FIG. 9 shows a method 2100 of using a classification model. In thisexample, the method comprises a step 2102 of obtaining a set ofintensity values for a sample spectrum. The method then comprises a step2104 of projecting the set of intensity values for the sample spectruminto PCA-LDA model space. Other classification model spaces may be used,such as PCA-MMC. The sample spectrum is then classified at step 2106based on the project position and the classification is then output instep 2108.

Classification of an aerosol, smoke or vapour sample will now bedescribed in more detail with reference to the simple PCA-LDA modeldescribed above.

FIG. 10 shows a sample spectrum obtained from an unknown aerosol, smokeor vapour sample. The sample spectrum has been pre-processed in order toderive a set of three sample peak-intensity values for respective massto charge ratios. As mentioned above, although only three samplepeak-intensity values are shown, it will be appreciated that many moresample peak-intensity values (e.g., ˜100 sample peak-intensity values)may be derived at many more corresponding mass to charge ratios for thesample spectrum. Also, as mentioned above, in other embodiments, thesample peak-intensity values may correspond to: masses; mass to chargeratios; ion mobilities (drift times); and/or operational parameters.

The sample spectrum may be represented by a sample vector d_(x), withthe elements of the vector being the peak-intensity values for therespective mass to charge ratios. A transformed PCA vector S_(x) for thesample spectrum can be obtained as follows:

d _(x) L=s _(x)  (5)

Then, a transformed PCA-LDA vector z_(x) for the sample spectrum can beobtained as follows:

s _(x) U=z _(x)  (6)

FIG. 11 again shows the PCA-LDA space of FIG. 8. However, the PCA-LDAspace of FIG. 11 further comprises the projected sample point,corresponding to the transformed PCA-LDA vector z_(x), derived from thepeak intensity values of the sample spectrum of FIG. 11.

In this example, the projected sample point is to one side of ahyperplane between the classes that relates to the right-hand class, andso the aerosol, smoke or vapour sample may be classified as belonging tothe right-hand class.

Alternatively, the Mahalanobis distance from the class centres in theLDA space may be used, where the Mahalanobis distance of the point z_(x)from the centre of class g may be given by the square root of:

(z _(x) −z _(g))^(T)(V′ _(g))⁻¹(z _(x) −z _(g))  (7)

and the data vector d_(x) may be assigned to the class for which thisdistance is smallest.

In addition, treating each class as a multivariate Gaussian, aprobability of membership of the data vector to each class may becalculated.

Library Based Analysis—Developing a Library for Classification

By way of example, a method of building a classification library usingplural input reference sample spectra will now be described.

FIG. 12 shows a method 2400 of building a classification library. Inthis example, the method comprises a step 2402 of obtaining plural inputreference sample spectra and a step 2404 of deriving metadata from theplural input reference sample spectra for each class of sample. Themethod then comprises a step 2406 of storing the metadata for each classof sample as a separate library entry. The classification library isthen output, for example to electronic storage, in step 2408.

A classification library such as this allows an aerosol, smoke or vapoursample to be classified using one or more sample spectra obtained fromthe aerosol, smoke or vapour sample. The library based analysis will nowbe described in more detail with reference to an example.

In this example, each entry in the classification library is createdfrom plural pre-processed reference sample spectra that arerepresentative of a class. In this example, the reference sample spectrafor a class are pre-processed according to the following procedure:

First, a re-binning process is performed. In this embodiment, the dataare resampled onto a logarithmic grid with abscissae:

$\begin{matrix}{x_{i} = \left\lfloor {N_{chan}\log{\frac{m}{M_{\min}}/\log}\frac{M_{m\alpha x}}{M_{\min}}} \right\rfloor} & (8)\end{matrix}$

wherein N_(chan) is a selected value and └x┘ denotes the nearest integerbelow x. In one example, N_(chan) is 2¹² or 4096.

Then, a background subtraction process is performed. In this embodiment,a cubic spline with k knots is then constructed such that p % of thedata between each pair of knots lies below the curve. This curve is thensubtracted from the data. In one example, k is 32. In one example, p is5. A constant value corresponding to the q % quantile of the intensitysubtracted data is then subtracted from each intensity. Positive andnegative values are retained. In one example, q is 45.

Then, a normalisation process is performed. In this embodiment, the dataare normalised to have mean {tilde over (y)}_(i). In one example, {tildeover (y)}_(i)=1.

An entry in the library then consists of metadata in the form of amedian spectrum value μ_(i) and a deviation value D_(i) for each of theN_(chan) points in the spectrum.

The likelihood for the i′th channel is given by:

$\begin{matrix}{{P{r\left( {\left. y_{i} \middle| \mu_{i} \right.,D_{i}} \right)}} = {\frac{1}{D_{i}}\frac{C^{C - {1/2}}{\Gamma(C)}}{\sqrt{\pi}{\Gamma\left( {C - {1/2}} \right)}}\frac{1}{\left( {C + \frac{\left( {y_{i} - \mu_{i}} \right)^{2}}{D_{i}^{2}}} \right)^{C}}}} & (9)\end{matrix}$

where ½ C<∞ and where Γ(C) is the gamma function.

The above equation is a generalised Cauchy distribution which reduces toa standard Cauchy distribution for C=1 and becomes a Gaussian (normal)distribution as C→∞. The parameter D_(i) controls the width of thedistribution (in the Gaussian limit D_(i)=σ_(i) is simply the standarddeviation) while the global value C controls the size of the tails.

In one example, C is 3/2, which lies between Cauchy and Gaussian, sothat the likelihood becomes:

$\begin{matrix}{{P{r\left( {\left. y_{i} \middle| \mu_{i} \right.,\ D_{i}} \right)}} = {\frac{3}{4}\frac{1}{D_{i}}\frac{1}{\left( {{3/2} + {\left( {y_{i} - \mu_{i}} \right)^{2}/D_{i}^{2}}} \right)^{3/2}}}} & (10)\end{matrix}$

For each library entry, the parameters μ_(i) are set to the median ofthe list of values in the i′th channel of the input reference samplespectra while the deviation D_(i) is taken to be the interquartile rangeof these values divided by √2. This choice can ensure that thelikelihood for the i′th channel has the same interquartile range as theinput data, with the use of quantiles providing some protection againstoutlying data.

Library Based Analysis—Using a Library for Classification

By way of example, a method of using a classification library toclassify an aerosol, smoke or vapour sample will now be described.

FIG. 13 shows a method 2500 of using a classification library. In thisexample, the method comprises a step 2502 of obtaining a set of pluralsample spectra. The method then comprises a step 2504 of calculating aprobability or classification score for the set of plural sample spectrafor each class of sample using metadata for the class entry in theclassification library. The sample spectra are then classified at step2506 and the classification is then output in step 2508.

Classification of an aerosol, smoke or vapour sample will now bedescribed in more detail with reference to the classification librarydescribed above.

In this example, an unknown sample spectrum y is the median spectrum ofa set of plural sample spectra. Taking the median spectrum y can protectagainst outlying data on a channel by channel basis.

The likelihood L_(s) for the input data given the library entry s isthen given by:

L _(s) =Pr(y|μ,D)=Π_(i=1) ^(N) ^(chan) ±Pr(y _(i)|μ_(i) ,D _(i))  (11)

wherein μ_(i) and D_(i) are, respectively, the library median values anddeviation values for channel i. The likelihoods L_(s) may be calculatedas log likelihoods for numerical safety.

The likelihoods L_(s) are then normalised over all candidate classes ‘s’to give probabilities, assuming a uniform prior probability over theclasses. The resulting probability for the class {tilde over (s)} isgiven by:

$\begin{matrix}{{P{r\left( \overset{˜}{s} \middle| y \right)}} = \frac{L_{\overset{\sim}{s}}^{({1/F})}}{\Sigma_{s}L_{s}^{({1/F})}}} & (12)\end{matrix}$

The exponent (1/F) can soften the probabilities which may otherwise betoo definitive. In one example, F=100. These probabilities may beexpressed as percentages, e.g., in a user interface.

Alternatively, RMS classification scores R_(s) may be calculated usingthe same median sample values and derivation values from the library:

$\begin{matrix}{{R_{s}\left( {y,\mu,D} \right)} = \sqrt{\frac{1}{N_{chan}}{\sum_{i = 1}^{N_{ch\alpha n}}\frac{\left( {y_{i} - \mu_{i}} \right)^{2}}{D_{i}^{2}}}}} & (13)\end{matrix}$

Again, the scores R_(s) are normalised over all candidate classes ‘s’.

The aerosol, smoke or vapour sample may then be classified as belongingto the class having the highest probability and/or highest RMSclassification score.

Raman Sampling System

FIG. 14 shows a Raman sampling system according to an embodiment andcomprises an excitation source 21, light delivery and collection optics22,24, a spectrograph 25 and a detector 26.

The Raman sampling system as shown in FIG. 10 comprises a Raman probe 20connected to a laser 21 (e.g. a diode laser 21) via a single opticaldelivery fibre 22. The delivery optical fibre 22 delivers laser lightfrom the diode laser 21 to a target 23 (which may comprise in vivobiological tissue). Scattered light from the target 23 is collected byone or more collection optical fibres 24 which may comprise a bundle ofoptical fibres. The scattered light is passed by the one or morecollection optical fibres 24 to a spectrograph 25. Raman spectra outputfrom the spectrograph 25 is recorded or detected by a charge-coupleddevice (“CCD”) camera or detector 26 and a signal is output to acomputer 27. The spectrograph 25 may comprise one or more holographicoptical elements to disperse the incident light onto a flat imagingplane that coincides with the detector 26. A CCD camera or detector 26may be placed in the image plane of the spectrograph 25 to capture thedispersed light and the resulting image may be displayed by the computer27.

Other embodiments are contemplated wherein the delivery fibre 22 maycomprise a plurality of delivery fibres 22.

The spectrograph 25 may comprise a transmissive imaging spectrographwith a volume phase holographic grating and the CCD camera or detector26 may according to an embodiment comprise a NIR optimisedback-illumination deep-depletion CCD array. The CCD may have a 16 bitdynamic range and may be liquid nitrogen cooled to −120° C. The f-numberof the spectrograph 25 (f=2.2) may be arranged to substantially matchthe numerical aperture (N.A.=0.22) of the one or more collection fibres24.

Laser light sources are preferred for Raman spectroscopy due to theirhigh power output and narrow bandwidth. For biological tissues a NIRlaser may be used because of its deep penetration depth and the lowerlevel of tissue autofluorescence under NIR excitation. 700-1000 μm maybe regarded as an optical window for biological tissues.

According to various embodiments the laser 21 may be arranged to emitlaser radiation at a wavelength of e.g. 632 nm, 690 nm, 785 nm, 810 nm,830 nm or 1064 nm. It will be understood, however, that otherembodiments are contemplated wherein the laser 21 may be arranged toemit laser radiation at other wavelengths. Shorter wavelengths may beused for ex vivo thin tissue samples. Both pulsed and continuous wave(CW) lasers may be used for Raman spectroscopy. For conventional Ramanspectroscopy continuous wave lasers are most commonly used.

The laser diode 21 may comprise an external-cavity stabilised diodelaser or a solid-state diode laser.

CCD detectors 26 are ideal for NIR Raman spectroscopy since they arelinear, have a good dynamic range and have a high quantum efficiency inthe NIR.

Raman spectroscopy utilises inelastically scattered laser light toprovide detailed information about vibrations of molecular bonds. TheRaman effect can be described as the inelastic scatter of light by themolecules of a sample. As a result, the energy of the scattered photons,and hence the wavelength, is different from that of the incidentphotons. These wavelength shifts are directly proportional to specificmolecular vibrational modes. A Raman spectrum, which is a plot ofintensity versus wavelength shift, provides information about themolecular constituents and microenvironment within a sample. Eachchemical moiety in a sample has a unique molecular structure.Accordingly, the composition of a sample can be determined throughanalysis of a Raman spectrum.

A Raman spectrum is a plot of intensity versus wavelength shift. Thewavelength shift is usually presented in units of relative wavenumbers(cm⁻¹). This is calculated for Stokes Raman scatter for light having anexcitation wavelength λ_(ex) and peak position A both in cm units:

$\begin{matrix}{{wavenumber}{= {\frac{1}{\lambda_{ex}} - \frac{1}{\lambda}}}} & (14)\end{matrix}$

Relative wavenumbers are used so that spectra collected with differentexcitation wavelengths can be compared with each other.

One advantage of Raman spectroscopy is that a typical Rama spectrum willcomprise relatively sharp peaks. This is in contrast to fluorescencespectroscopy where there are a limited number of fluorophores and thebroad peaks make it harder to extract parameters from the unresolvedspectral features. In fact, much of the structure of fluorescencespectra of biological tissue is due to the spectral contributions ofoxyhemoglobin and deoxyhemoglobin rather than fluorescence.

Unlike infra-red absorption spectroscopy, water does not have an adverseeffect on Raman spectra. Therefore, hydrated samples such as in vivotissue may be studied and no sample preparation is required.

It can be shown from classical theory that the magnitude of thefrequency shift is equal to the frequency of the participating molecularvibrational modes. Light scattered with decreased frequency, and hence alonger wavelength, is referred to as Stokes Raman scatter whilst theconverse is referred to as anti-Stokes Raman scatter. At roomtemperature anti-Stokes Raman scatter is much weaker than Stokes Ramanscatter.

Absorbed light will shift a molecule to an excited energy level. In thecase of Rayleigh (elastic) scatter, light is absorbed, the molecule isexcited from a ground state n₀ to a second excited level n₂, and thenthe molecule relaxes directly back from the second excited level n₂ tothe ground state n₀ with a photon being emitted and without an exchangeof energy.

Stokes Raman scatter occurs after absorption of an incident photonwhereupon the molecule is excited from the ground state n₀ to the secondexcited level n₂ and then the molecule relaxes from the second excitedlevel n₂ to an intermediate first vibrational energy level n₁ which isabove the ground state n₀.

If the molecule is already in an intermediate first excited vibrationalenergy level n₁ then an incident photon may cause excitation up to thesecond excited energy level n₂ with subsequent relaxation down to theground state n₀ resulting in anti-Stokes Raman scatter of the incidentphoton with reduced wavelength.

The delivery optical fibre 22 may terminate with a short wavelength passor a bandpass (first) filter. The first filter may be arranged totransmit laser excitation light from the diode laser 21 but block longerwavelength spectral background from the delivery optical fibre 22. Thedelivery optical fibre 22 may be multi-mode and have a core diameter of100-200 μm. The delivery optical fibre 22 may according to an embodimenthave a numerical aperture in the range 0.22-0.37.

The delivery optical fibre 22 may comprise a high-hydroxide (“high-OH”)fibre having a high UV and visible wavelength transmission.Alternatively, the delivery optical fibre 22 may comprise alow-hydroxide (“low-OH”) fibre for use in the NIR and IR wavelengthrange.

The one or more collection optical fibres 24 may be preceded by a longwavelength pass or notch (second) filter. The second filter may bearranged to transmit a Raman spectrum from the target 23 (e.g., tissue)whilst blocking laser light which may be backscattered from the surfaceof the target 23.

According to various embodiments inline bandpass or long pass filtersmay be deposited on the optical fibre tips to reduce noise.

According to an embodiment excitation laser light emitted by thedelivery optical fibre 22 may pass through a collimating lens, abandpass filter (e.g. 785±2.5 nm) and a focusing lens. The bandpassfilter effectively rejects Raman scattering and fluorescence which mayhave arisen from within the delivery optical fibre 22.

The intensity of the laser 21 may be controlled so that the irradianceat the target does not exceed a desired limit. For example, according toan embodiment the irradiance on the surface of skin (or other tissue)may be kept below 1.63 W/cm² for a 785 nm laser beam in accordance withANSI Standard Z136.1-1993 (American National Standards Institute).

According to another embodiment the excitation laser light may have awavelength of 830 nm and be generated by a diode laser 21. However,other embodiments are contemplated wherein other types of lasers may beused and the wavelength of the laser may be varied.

According to an embodiment backscattered Raman light may be collectedusing an f/1.2 camera lens having, for example, a focal length of 50 mm.The camera lens may be arranged to collimate the Raman light before theRaman light is notch filtered and then focused onto a f/4 spectrograph25 via a lens for detection by the CCD camera or detector 26.

According to another embodiment the backscattered Raman light may becollected by a double lens arrangement wherein the first lens is forsignal collection and beam collimation and the second lens is forfocusing the signal into the collection optical fibres 24. The lensesmay be arranged to have a focal length of 50 mm and to have a numericalaperture (NA) which substantially matches that of the collection opticalfibre 24.

A longpass filter may be located between the first and second lenses.According to an embodiment the longpass filter may comprise aninterference filter having a pass band 800-1200 nm. The longpass filtermay be arranged to attenuate elastically scattered light whilst allowingpassage of Raman scattered light.

The excitation light may be focused down to a spot size of approximately100 μm diameter and the diameter of the collection fibre 24 may beapproximately 1 mm.

The excitation optical fibre 22 and/or the collection optical fibre 24may be fabricated from glass or from sapphire. Sapphire is of particularinterest since it exhibits no fluorescence and only has a single sharpRaman band in normal regions of interest. Sapphire is also hard anddurable.

According to an embodiment the Raman probe 20 may comprise a singlecentral excitation fibre having e.g. a 200 μm diameter core which may beprovided with an aluminium jacket for optical isolation so as to preventcross talk with a plurality of collection fibres which may be arrangedin a circular fashion around the central excitation fibre.

The collection fibres which may be arranged around the centralexcitation fibre may result in a probe having an overall diameter of1.75 mm. The bundle of fibres may be encased in a black Teflon® coatingfor binding and protection and the Raman probe may have an overalllength of approx. 4 m.

The Raman probe 20 may be provided in various different configurations.For example, according to an embodiment the Raman probe 20 may comprisea single ring of collection fibres 24 provided around a single centralexcitation fibre 22. Alternatively, according to another embodiment theRaman probe 20 may comprise a double ring of collection fibres 24provided around a single central excitation fibre 22.

The single or double ring of collection fibres 24 may, for example,comprise 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or >20collection fibres.

According to another embodiment the collection optical fibres 24 maycomprise a collection of 5-10, 10-20, 20-30, 30-40, 40-50, 50-60 or >60low-OH fibres (100 μm core diameter).

The excitation laser may have a power of −100 mW and the Raman probe 20may be operated so that the one or more collection fibres 24 collectRaman light for a period of time of e.g. approx. 1 s, 2 s, 5 s, 10 s, 20s, 30 s, 40 s, 50 s or 60 s.

The Raman probe 20 may be arrange to record Raman light having awavenumber in the range of 800 to 1800 cm⁻¹. However, it will beunderstood by those skilled in the art that the range of 800 to 1800cm⁻¹ should not be construed as being limiting. For example, accordingto other various embodiments Raman features or shifts in the range from600 to 2000 cm⁻¹ may be determined.

According to various embodiments the Raman probe 20 may comprise an invivo Raman spectroscopy system (“IVRS”) and the Raman probe 20 may beused as part of an endoscopic tool.

For example, according to an embodiment the Raman probe 20 may be usedas an in vivo endoscopic tool for obtaining Raman spectra from humangastrointestinal tissues.

According to an embodiment the Raman probe 20 may utilise a 785 nm lasersource and the laser light may be arranged to have a power of 100 mW.Raman spectra may be obtained during a collection time of e.g. 5 s.

According to an embodiment calcium fluoride (CaF₂) optical windows andother optical components may be used since CaF₂ has an excellent Ramanwindow since it has a high transmission in the NIR, a low Ramanscattering cross section which produces a single weak peak at 320 cm⁻¹and a refractive index of −1.4 which approximately matches the index ofrefraction of tissue.

Raman System Initialisation

The Raman system may be calibrated prior to clinical use. For example,the Raman system may be wavelength calibrated and the system spectralresponse may also be calibrated. The Raman signal may be subjected tointensity calibration and the CCD signal emitted from the CCD camera 26may be processed to effect dark noise subtraction. The CCD dark noisemay be measured before each measurement and may then be sequentiallysubtracted immediately after each CCD readout event.

Wavelength calibration may be performed using cyclohexane, acetone andbarium sulfate in combination with an Hg—Ar lamp. A fifth orderpolynomial fitting may be used to correlate the CCD pixels with thewavelengths.

The computer 27 may be arranged to load databases and files needed forPCA and LDS analysis of the Raman spectra and/or associated massspectra.

Various known algorithms may be applied to the obtained Raman spectra inorder to remove any NIR autofluorescence background which may besuperimposed upon the Raman signal.

Raman Spectroscopy and Analysis of Skin Cancer

Human skin may be analysed using non-invasive optical techniquesincluding infrared (IR) spectroscopy and Raman spectroscopy. IR andRaman spectroscopy are similar in that they both probe the vibrationalproperties of molecules according to differing underlying physicalprinciples. IR spectroscopy is based on the absorption properties of thesample tissue where the signal intensity follows Beer's law whereasRaman spectroscopy relies on detecting photons which are scatteredinelastically by the sample tissue. The intensity of the Raman shift isdirectly proportional to molecular concentration and is independent ofsample thickness.

It is known that Raman analysis of skin tissue results in prominentspectral features being observed in the range 800-1800 cm⁻¹ and inparticular major vibrational bands around 855 cm⁻¹, 938 cm⁻¹, 1002 cm⁻¹,1080 cm⁻¹, 1269 cm⁻¹, 1301 cm⁻¹, 1445 cm⁻¹, 1655 cm⁻¹ and 1745 cm⁻¹. Thestrongest band is located around 1445 cm⁻¹ and is assigned to the CH₂deformations of proteins and lipids. The 1655 cm⁻¹ and 1269 cm⁻¹ bandsare assigned to protein vibrational modes involving amide I and amideIII.

It is also known that Raman analysis of skin shows major Raman peaksaround 851 cm⁻¹, 962 cm⁻¹, 1065 cm⁻¹, 1258 cm⁻¹, 1297 cm⁻¹, 1437 cm⁻¹,1542 cm⁻¹, 1653 cm⁻¹, 1737 cm⁻¹, 2159 cm⁻¹, 2698 cm⁻¹, 2828 cm⁻¹, 2879cm⁻¹ and 2987 cm⁻¹.

Basal cell carcinoma (“BCC”) originates in the kertatinocytes of theepidermis. It is known that NIR Raman spectra of basal cell carcinomatissue samples show an intensity decrease of the amide III region at1230-1290 cm⁻¹ relative to the lipid region at 1290-1330 cm⁻¹. Adecrease in intensity may also be observed at the amino acid region of830-900 cm⁻¹ and 900-990 cm⁻¹. In particular, the following spectralregions have been found to differ with pathology: 900-984 cm⁻¹ (aminoacids), 1290-1350 cm⁻¹ (lipids), 1600-1725 cm⁻¹ (amide I) and 2800-3000cm⁻¹ (C—H region).

Raman spectra of skin tissue exhibit collagen features from the dermisdue to proline and hydroxyproline side chain peaks at 855 cm⁻¹ and 936cm⁻¹.

It is apparent, therefore, that Raman spectra may be used to helpidentify potentially cancerous skin tissue in combination with analysisusing an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Gynaecological Cancer

It is known that the relative intensities of peaks around 1262 cm⁻¹(amide III), 1445 cm⁻¹ (CH bend) and 1659 cm⁻¹ (amide I) may be used toclassify normal and malignant gynaecological tissue.

For uterine and cervical cancers the intensity of a peak around 1657cm⁻¹ may be reduced relative to the 1445 cm⁻¹ band possibly due tochanges in the protein-lipoprotein composition of the tissue.

A broadening of the amide III band for uterine, endometrial and ovariancancers is also observed and may be indicative of a degradation in theelastin content.

It is apparent, therefore, that Raman spectra may be used to helpidentify potentially cancerous or diseased gynaecological tissue incombination with analysis using an ambient ionisation ion source.

Ultraviolet Resonance Raman Spectroscopy (“UVRRS”)

Ultraviolet resonance Raman spectroscopy (“UVRRS”) relates to a variantof Raman spectroscopy wherein when the excitation wavelength matches anabsorption band of the sample then the intensity of the Raman signal isincreased by several orders of magnitude. As a result, the signal tonoise ratio is dramatically increased and tissue fluorescence may alsobe circumvented.

Embodiments are contemplated wherein ultraviolet resonance Ramanspectroscopy data may be acquired and used to help identify potentiallycancerous or diseased tissue in combination with analysis using anambient ionisation ion source.

Raman Spectroscopy and Analysis of Breast Tissue

Breast tissue is an excellent candidate for Raman spectroscopy since ithas a high concentration of fatty acids which produces a strong Ramanscatter and results in spectra which have an excellent signal to noiseratio (“SNR”).

It has been shown, for example, that it is possible to use Ramanspectroscopy to detect silicone (polydimethylsiloxane gel) in lymphnodes due, for example, to leakage of breast implants with subsequentleakage and contamination of the lymph nodes.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help identify potentially cancerous, diseased orcontaminated breast tissue in combination with analysis using an ambientionisation ion source.

Raman Spectroscopy and Analysis of Formalin Fixed Tissues

Raman spectroscopy may be used to analyse both formalin andparaffin-fixed tissue samples. Fixing a tissue sample with formalinintroduces spectral contamination of an additional band around 1040cm⁻¹.

Raman spectroscopy may also be performed on tissue samples which havebeen stored frozen. Tissue samples may be freeze stored at −85° C. inoptimal-cutting temperature (“OCT”) media. Prior to analysis by Ramanspectroscopy, the tissues should be pre-thawed at room temperature for15 min, removed from the OCT and immersed in phosphate buffered saline(“PBS”) for an additional 15 minutes. Raman spectroscopy may then beperformed on the sample immersed in PBS.

Embodiments are therefore contemplated wherein Raman spectroscopy datamay be acquired and used to help analyse ex vivo tissue includingformalin fixed and frozen fixed tissue in combination with analysisusing an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Bone and Skull

Bone consists of hydrated inorganic extracellular matrices of carbonatedcalcium phosphates that are rich in collagen. The organic component alsoincludes small amounts of glycosaminoglycans, glycoproteins, lipids andpeptides. Conventional X-ray diffraction analysis of bone has a numberof drawbacks whereas Raman spectroscopy may be used to obtain data bothfrom the organic and inorganic components of bone.

Characteristic Raman peaks of skull are observed at around 800 cm⁻¹, 851cm⁻¹, 950 cm⁻¹, 1065 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1653 cm⁻¹,1725 cm⁻¹, 2139 cm⁻¹ and 2917 cm⁻¹.

Both skull and teeth have a strong Raman peak around 950 cm⁻¹ comingfrom calcium hydroxylapatite.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse bone and skull in combination withanalysis using an ambient ionisation ion source.

According to various embodiments biological tissue or portions of boneor skull may be irradiated using a laser in order to generate an aerosolor surgical smoke. The aerosol or surgical smoke may then be analysedusing laser induced breakdown spectroscopy (“LI BS”).

Raman Spectroscopy and Analysis of Teeth

The major hard component of teeth is dentine which bound by cementum atthe root and a thin layer of enamel at the exposed crown. Thesematerials are composed of approximately 70% inorganic apatite within anorganic matrix that is predominantly collagen I. Smaller concentrationsof protein, lipids and peptides are also present. Enamel, the hardesttissue in the human body, has the lowest concentration of organic matterand does not contain collagen.

NIR Raman spectroscopy can provide information about both the mineraland organic components of teeth.

Characteristic Raman peaks of teeth are observed around 800 cm⁻¹, 851cm⁻¹, 950 cm⁻¹, 1065 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1653 cm⁻¹,1725 cm⁻¹, 2139 cm⁻¹ and 2917 cm⁻¹.

Both skull and teeth have a strong Raman peak around 950 cm⁻¹ comingfrom calcium hydroxylapatite.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse teeth in combination with analysisusing an ambient ionisation ion source.

According to various embodiments biological tissue or portions of teethmay be irradiated using a laser in order to generate an aerosol orsurgical smoke. The aerosol or surgical smoke may then be analysed usinglaser induced breakdown spectroscopy (“LI BS”).

Raman Spectroscopy and Analysis of Blood, Blood Pellets and Serum

Raman spectra generated from blood and blood pellets are near identicaland suggest that the observed spectral features are due mainly to redblood cells. Major Raman peaks are observed around 742 cm⁻¹, 778 cm⁻¹,991 cm⁻¹, 1074 cm⁻¹, 1120 cm⁻¹, 1160 cm⁻¹, 1210 cm⁻¹, 1335 cm⁻¹, 1383cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1614 cm⁻¹, 2159 cm⁻¹ and 2914 cm⁻¹. Highlyoxygenated blood also shows additional peaks around 1375 cm⁻¹, 1590 cm⁻¹and 1640 cm⁻¹.

Serum exhibits major Raman peaks around 820 cm⁻¹, 1044 cm⁻¹, 1335 cm⁻¹,1383 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1614 cm⁻¹, 1653 cm⁻¹, 2159 cm⁻¹, 2646cm⁻¹ and 2914 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse blood, blood pellets and serum incombination with analysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Adipose Tissue and Fatty Acids

Adipose tissue is loose connective tissue composed of adipocytes and itsmain role is to store energy in the form of fat. Adipose tissue exhibitscharacteristic Raman peaks around 1065 cm⁻¹, 1270 cm⁻¹, 1298 cm⁻¹, 1437cm⁻¹ and 1650 cm⁻¹ in the low frequency region and peaks around 2828cm⁻¹, 2879 cm⁻¹ and 2970 cm⁻¹ in the high frequency region.

Palmitic acid is one of the most common saturated fatty acids found inanimals and plants and occurs mainly as its ester in triglycerides(fats). All saturated fatty acids including lauric acid, myristic acid,palmitic acid and stearic acid have similar Raman spectra with strongpeaks around 1063 cm⁻¹, 1128 cm⁻¹, 1296 cm⁻¹ and 1438 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse adipose tissue and fatty acids incombination with analysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Skeletal Muscles

Skeletal muscles comprise contractile tissue and the characteristicRaman peaks of skeletal muscles are located around 851 cm⁻¹, 962 cm⁻¹,1065 cm⁻¹, 1258 cm⁻¹, 1297 cm⁻¹, 1437 cm⁻¹, 1542 cm⁻¹, 1653 cm⁻¹ and1737 cm⁻¹ in the low frequency region and around 2159 cm⁻¹, 2698 cm⁻¹,2828 cm⁻¹, 2914 cm⁻¹ and 2987 cm⁻¹ in the high frequency region.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse skeletal muscles in combination withanalysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Brain Disease

Raman spectroscopy has been used to study both normal and diseased braintissue. Brain tissue comprises approximately 70% protein, 12% lipid and3-5% nucleic acid by dry weight and provides a strong Raman signal withNIR excitation.

Parkinson's disease is a progressive neurological disorder which resultsfrom the degeneration of the substantia nigra (“SN”) in the basalganglia.

Glioblastoma multiforme (“GBM”), which originate from glial cells, arethe most severe malignant brain tumours due to their invasive nature andhigh morbidity. Diagnosis and grading is dependent upon the tumourorigin, mitotic activity and endothelial proliferation. Conventionalgrading of brain tumours relies on biopsies which carries a risk ofbleeding and subsequent brain damage.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse brain disease in combination withanalysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Gastrointestinal (GI) Tract Diseasesand Disorders

Barrett's esophagus (“BE”) is a premalignant condition where normalsquamous spithelium (SQ) lining is replaced with glandular columnarepthelium. Patients with BE have an increased risk of developingesophageal adenocarcinoma (AC). Dysplasia (DYS), defined as unequivocalneoplastic epithelium, is an important marker for an increased risk ofmalignancy.

Characteristic Raman peaks of normal stomach tissue are observed around828 cm⁻¹, 851 cm⁻¹, 991 cm⁻¹, 1044 cm⁻¹, 1258 cm⁻¹, 1302 cm⁻¹, 1442cm⁻¹, 1653 cm⁻¹, 1725 cm⁻¹, 2139 cm⁻¹, 2177 cm⁻¹ and 2917 cm⁻¹.

Characteristic Raman peaks of normal small intestine tissue are observedaround 828 cm⁻¹, 921 cm⁻¹, 991 cm⁻¹, 1044 cm⁻¹, 1258 cm⁻¹, 1074 cm⁻¹,1160 cm⁻¹, 1258 cm⁻¹, 1302 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1653cm⁻¹, 1725 cm⁻¹, 2139 cm⁻¹, 2177 cm⁻¹, 2870 cm⁻¹ and 2917 cm⁻¹.

Characteristic Raman peaks of normal colorectal tissue are observedaround 1080 cm⁻¹, 1260 cm⁻¹, 1300 cm⁻¹, 1450 cm⁻¹, 1650 cm⁻¹ and 1750cm⁻¹.

Characteristic Raman peaks of normal bladder tissue are observed around828 cm⁻¹, 921 cm⁻¹, 1044 cm⁻¹, 1442 cm⁻¹, 1653 cm⁻¹, 1725 cm⁻¹, 2139cm⁻¹ and 2917 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse gastrointestinal (GI) tract diseasesand disorders in combination with analysis using an ambient ionisationion source.

According to various embodiments biological tissue or portions ofgastrointestinal tract may be irradiated using a laser or a rapidevaporative ionisation mass spectrometry (“REIMS”) ionisation source inorder to generate an aerosol or surgical smoke.

Raman Spectroscopy and Analysis of Lung Tissue

Characteristic Raman peaks of lung tissue are observed around 800 cm⁻¹,991 cm⁻¹, 1044 cm⁻¹, 1302 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1590cm⁻¹, 1614 cm⁻¹, 1653 cm⁻¹, 1725 cm⁻¹, 2139 cm⁻¹ and 2917 cm⁻¹. Lungtissue has a special characteristic peak at 1590 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse lung tissue diseases in combinationwith analysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Colorectal Cancers

Colorectal cancers following a similar progression of disease to that ofgastrointestinal cancers and begins with dysplasia. Subtle changes inthe bands around 1340 cm⁻¹, 1458 cm⁻¹, 1576 cm⁻¹ and 1662 cm⁻¹ areindicative of an increase in both the nucleic acid and lipid content foradenocarcinoma.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse colorectal cancers in combination withanalysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Kidney, Liver and Spleen Tissue

Characteristic Raman peaks of kidney tissue are observed around 876cm⁻¹, 1031 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1623 cm⁻¹, 1653 cm⁻¹,1725 cm⁻¹, 2127 cm⁻¹, 2159 cm⁻¹ and 2914 cm⁻¹.

Characteristic Raman peaks of liver tissue are observed around 851 cm⁻¹,1044 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1585 cm⁻¹, 1623 cm⁻¹, 1653cm⁻¹, 1725 cm⁻¹, 2159 cm⁻¹, 2870 cm⁻¹ and 2914 cm⁻¹.

Characteristic Raman peaks of spleen tissue are observed around 828cm⁻¹, 1017 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1623 cm⁻¹, 1725 cm⁻¹, 2127 cm⁻¹,2151 cm⁻¹, 2747 cm⁻¹ and 2914 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse kidney, liver and spleen tissue incombination with analysis using an ambient ionisation ion source.

Brain Tumours

The brain is the centre of the nervous system and comprises two broadclasses of cells namely neurons and glia.

Brain tissue has characteristic Raman peaks around 962 cm⁻¹, 991 cm⁻¹,1044 cm⁻¹, 1302 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1614 cm⁻¹, 1653 cm⁻¹, 1725cm⁻¹, 2139 cm⁻¹, 2879 cm⁻¹ and 2917 cm⁻¹. Brain tissue has a stronglipid peak around 2879 cm⁻¹.

Brain tumours have been induced in mice by injecting a suspension of theD-54MG malignant human glioma cell line into severe compromised immunedeficient (scid) mice. Possible glioma markers were identified by Ramanspectroscopy at around 1158 cm⁻¹, 1362 cm⁻¹, 1390 cm⁻¹ and 1550 cm⁻¹.

Human brain tumours have also been studied using Raman spectroscopy. Ithas been observed that the amide III band shifts from 1245 to 1268 cm⁻¹in glioma grade III brain tumours which is indicative of a change fromα-helix to random coil secondary protein structure. The tumours alsohave an enhanced peak at 1130 cm⁻¹ (C—C stretch) due to the transconfiguration of the lipid hydrocarbon chains which suggested a loss offluidity of these lipids which was also reflected in the lipid peaks ofthe CH stretching region at 2800-2950 cm⁻¹. It has also been observedthat the polysaccharide peak at 856 cm⁻¹ is enhanced for tumours and maybe used to monitor tumour development.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse brain tumours in combination withanalysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Arteries and Heart Tissue

Heart attacks, which result mostly from coronary atherosclerosis,account for approximately 20-25% of all deaths in the United States.Arteries are composed of three layers namely the intima, media andadventitia. Atherosclerosis occurs when the intima thickens due anincrease in the collagen content. This results in the build up of fatsand necrotic tissue, which if left unchecked, results in the formationof plaques. Subsequent accumulations of calcium may result in calciumhydroxyapatite deposits in the artery wall which may further occludeblood flow and result in conditions such as heart disease.

Normal aorta are dominated by protein peaks at 1252 cm⁻¹, 1452 cm⁻¹ and1658 cm⁻¹. Raman spectra of atheromatous plaques exhibit many peaksbelow 1000 cm⁻¹ which are attributed to cholesterol. Peaks are alsoobserved at 630 cm⁻¹ and 1070 cm⁻¹ which correlate with calciumhydroxyapatite and carbonate apatites respectively.

Atherosclerotic aorta has been observed to comprise 47% totalcholesterol (c.f. 6% for normal tissue).

Characteristic Raman peaks of heart tissue are observed around 962 cm⁻¹,1031 cm⁻¹, 1302 cm⁻¹, 1335 cm⁻¹, 1442 cm⁻¹, 1542 cm⁻¹, 1623 cm⁻¹, 1653cm⁻¹, 1725 cm⁻¹, 2127 cm⁻¹, 2159 cm⁻¹, 2870 cm⁻¹ and 2914 cm⁻¹.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse arteries and heart tissue incombination with analysis using an ambient ionisation ion source.

Raman Spectroscopy and Analysis of Organs

Main Raman peaks coming from proteins, lipids and DNS appear in similarpositions of Raman spectra of all tissues because all tissues haveprotein molecules, phospholipids, DNA and RNA. Raman peaks around 1270cm⁻¹, 1310 cm⁻¹, 1445 cm⁻¹, 1660 cm⁻¹ and 2900 cm⁻¹ originate fromlipids and proteins and are clearly observed in every organ.

Embodiments are contemplated wherein Raman spectroscopy data may beacquired and used to help analyse organ tissue in combination withanalysis using an ambient ionisation ion source.

Fluorescence Background Tissue

Autofluorescence background can influence the measurement of Ramanspectra from organs. The main fluorophores in biological tissue arepyridinic (NADPH) and flavin coenzymes (FAD), collagen and elastin.

Contrast Agents and Nanoparticles

The near-infrared (“NIR”) may be used to interrogate tissues incombination with NIR excitable dyes or contrast agents.

Various embodiments are contemplated wherein endogenous or exogenouscontrast agents may be used to enhance image data, physical data,chemical data or other data which may be acquired according to variousembodiments.

A number of different contrast agents may be used to enhance image data,physical data, chemical data or other data which, for example, mayfluorescence when illuminated with infrared radiation having awavelength in the range 700-900 nm. The wavelength range 700-900 nm maybe considered to comprise a therapeutic window since in vivo tissueexhibits a low absorbance in this wavelength range. Absorption occursprimarily from tissue chromophores of oxy- and deoxyhemoglobin, fat,melanin and water.

It will be understood that the ability to detect potentially abnormal ordiseased tissue by imaging, chemical, physical or other techniquesdepends principally upon there being a contrast between healthy anddiseased tissue.

Alternatively, abnormal or diseased tissue can be differentiated fromhealthy tissue on the basis of the two different tissue types havingdifferent scattering properties.

Although the wavelength range 700-900 nm is of particular interest dueto the low absorbance in this wavelength range, infrared radiation inthis wavelength range can also exhibit a relatively high scatteringcoefficient.

Embodiments are contemplated wherein imaging data, chemical data,physical data or other data may be obtained by detecting differences inthe scattering of infrared radiation within the wavelength range 700-900nm between healthy and diseased tissue. Embodiments are alsocontemplated wherein one or more exogenous contrast agents may be usedto analyse in vivo, ex vivo or in vitro tissue samples, biologicalmatter, organic matter (including plastics), one or more bacterialcolonies or one or more fungal colonies. According to an embodiment oneor more exogenous fluorescence contrast agents may be provided or addedto the tissue in order to augment endogenous contrast. The one or morecontrast agents may comprise one or more fluorescent contrast agents.

The one or more contrast agents may comprise one or more visible dyes.

The one or more contrast agents may comprise one or more radiocontrastagents.

The one or more contrast agents may comprise one or more optical, nearinfrared (“NIR”), fluorescent, autofluorescent or diagnostic contrastagents.

According to various embodiments the one or more contrast agents may beselected from the group consisting of: (i) indocyanine green (“ICG”) andderivatives or conjugates of indocyanine green includingindotricarbocyanine; (ii) diethylthiatricarbocyanine iodide (“DTTCI”)and derivatives or conjugates of diethylthiatricarbocyanine iodide;(iii) rhodamine B and derivatives or conjugates of rhodamine B; (iv)photodynamic therapy (“PDT”) agents including hexylpyropheophorbide(“HPPH”); (v) a cyanine dye including Cy 5.5 dyes; and (vi) bifunctionalcontrast agents.

Indocyanine green (“ICG”) is of particular interest since it has FDAapproval for systemic administration. Indocyanine is excited at about780 nm and emits at 830 nm. Indocyanine green will dissolve in blood andwill bind to proteins such as albumin and lipoproteins. ICG is anonspecific agent and is cleared rapidly from the blood. However, ICGtends to collect in regions of dense vascularity through extravascation.ICG may be administered to a patient at a dose of 0.2 mg/kgintravenously. Derivatives and conjugates of ICG may also be used.

Various embodiments are contemplated wherein ICG is excited using a 780nm laser and fluorescent spectra at 830 nm are detected using a gainmodulated image intensified charge coupled camera (ICCD).

Other embodiments are contemplated wherein magnetic nanoparticles (“MNPs”) may be used as a contrast agent. The magnetic nanoparticles maycomprise ferromagnetic iron oxide i.e. magnetite (Fe₃O₄) or maghemite(γ-Fe₂O₃) having a diameter in the range 1-100 nm. According to anembodiment the nanoparticles may have a diameter in the range 1-10,10-20, 20-30, 30-40, 40-50, 50-60, 60-70, 70-80, 80-90 or 90-100 nm. Inparticular, various embodiments are contemplated wherein nanoparticleshaving a core diameter in the range of 5-15 nm may be used as contrastagents. In particular, as the size of the nanoparticles is reduced thenthe characteristics of the nanoparticles changes from havingmulti-domain ferromagnetic characteristics to having single domaincharacteristics and finally to having superparamagnetic characteristics.In particular, small nanoparticles having a diameter in the range 5-15nm exhibit superparamagnetic properties having no hysteresis losses andwill generate heat as a result of relaxational losses, mainly Neelrelaxation loss. The inherent ferromagnetic properties of magneticnanoparticles provides contrast enhancement with magnetic resonance(“MR”) imaging. For example, accumulation of magnetic nanoparticles inbrain tumours appears as a hypointensity on T2-weighted imagingincluding gradient echo imaging.

Magnetic nanoparticles may also be functionalised to target cancer cellsthereby enabling cancerous tissue to be identified by magnetic resonanceimaging.

According to an embodiment ultrasmall superparamagnetic iron oxidenanoparticles (“USPIONPs”) may be used.

In addition to using nanoparticles to accumulate within canceroustissue, according to further embodiments the nanoparticles may be heatedby applying a magnetic field and in particular an alternating magneticfield (“AMF”) which produces heat via relaxational loss via the BrownianNeel relaxation process or by hysteresis loss. As a result, potentiallycancerous tissue can be identified on the basis of having an elevated orhyperthermic temperature relative to surrounding normal healthy tissue.Accordingly, thermal detection techniques in conjunction with theheating of nanoparticles which have accumulated in cancerous tissue maybe used to visualise, image or target potentially cancerous tissue.

Further embodiments are contemplated wherein nanoparticles which haveaccumulated in cancerous tissue may be heated up to temperatures >40° C.in order to selectively target and kill cancerous cells. For example,heating cancerous cells to a temperature around 45° C. can cause cancercells to undergo apoptosis or necrosis. Furthermore, locally heatingcancerous cells can increase the blood flow to the cancerous cells whichcan, for example, result in an improved delivery of chemotherapeuticagents to the cancerous cells. Also, cancer cells are more heatsensitive than normal tissue and so heat can be selectively applied tocancer cells in order to kill cancer cells without damaging surroundingnormal or healthy tissue.

According to an embodiment the nanoparticles may comprise a polysiloxanematrix (Si) wherein chelating species such as diethylene triaminepentaacetic acid (DTPA) at the surface of the particles allows thecomplexation of metallic elements such as gadolinium (Gd), silicon (Si),calcium (Ca) and iron (Fe).

According to other embodiments the nanoparticles may be heated byradiofrequency capacitive heating wherein, for example, an alternatingelectrical current at 8 MHz may be applied and the temperature oftissues located between the electrodes increases. Magnetite cationicliposomes (MCLs) may be used and when injected into cancer cells thecancerous tissue may reach a temperature which is 2-3° C. above that ofhealthy tissue.

Other embodiments are contemplated wherein antibodies containing aferromagnetic component may be used as a contrast agent.

The one or more contrast agents may be exogenous or endogenous to thetarget.

As is well known, fluorophores may be activated to an excited state byabsorbing a photon and may then relax to a ground state in anon-radiative manner. Alternatively, the fluorophore may relax to theground state in a radiative (fluorescence) manner. The fluorescencelifetime T is equivalent to the mean time that a fluorophores remains inits activated state and the quantum efficiency is the proportion ofrelaxations which occur radiatively.

Other mechanisms are known wherein the excited state can undergointersystem crossing to an intermediate excited state wherein the spinstate of the electron is flipped and the relaxation of the intermediateexcited state is forbidden until the electron spin is reversed. Thelifetimes of the intermediate excited state may be of the order ofmicroseconds to milliseconds and are termed phosphorescence.

Fluorescence radiative decay can be affected by pH, oxygenation, freeion concentrations, glucose and other analytes. Fluorescence cantherefore provide an optical imaging ability which is not otherwisedirectly detectable.

According to an embodiment the fluorescence spectra of tissue may beanalysed in order to determine the pH, oxygenation level or quantumefficiency of the tissue.

Other embodiments are contemplated wherein gamma ray imaging may beperformed and optionally a technetium-99 sulfur colloid may be injectedinto the target tissue for analysis.

According to various embodiments gold nanoparticles (“Au NPs” or “GNPs”)may be used as contrast agents. Gold nanoparticles may be formed by alaser ablation method wherein a gold target in water is subjected topulsed laser irradiation. Colloidal gold can also be prepared by citratereduction. Various other physical methods of producing goldnanoparticles are known including inert gas condensation, thermolysis ofgold(I) complex, radiolysis of gold salts, photochemistry andsonochemistry. Chemical methods of producing gold nanoparticles areknown including emulsification, reduction of gold ions in the presenceof a disperant, seed-mediated growth, use of reverse micelles and phasetransfer reactions. Gold nanoparticles may also be biosynthesised bycertain types of fungi including Fusarium oxysporum, Verticillium sp.and Colletotrichum sp. Gold nanoparticles have also been synthesizedwithin HEK-293, HeLa, SiHa and SKNSH cells.

Gold nanoparticles may be readily functionalised generally through thiollinkages to provide functionalised gold nanoparticles (fGNPs) Thesurface of gold nanoparticles may be functionalised with e.g.cyclodextrin as a drug pocket having hydrophobic cavities, antibodies asa targeting moiety and poly(ethleneglycol) (PEG) as an anti-foulingshell. Anti-cancer drugs may be encapsulated into the hydrophobic cavityof the cyclodextrin and the gold nanoparticles may therefore be used asa drug delivery system (DDS).

According to various embodiments gold nanoparticles and in particularfunctionalised gold nanoparticles as described above may be used ascontrast agents.

Gold nanoparticles cause local heating when irradiated with light(800-1200 nm) and hence gold nanoparticles may be used in thephotothermal destruction of tumours according to various embodiments.

Plasmonic gold nanoparticles may be used for cancer diagnosis andphotothermal therapy. Surface plasmon resonance (“SPR”) leads to strongelectromagnetic fields on the surface of gold nanoparticles whichenhances all radiative properties such as absorption and scattering. Inparticular, Raman scattering is enhanced. Additionally, stronglyabsorbed light may be quickly converted to heat via a series ofnonradiative processes.

Gold nanoparticles can be optically tuned by shape and structure and forexample gold nanorods having different optical properties to goldnanospheres can be produced. The aspect ratio can be preciselycontrolled by changing experimental parameters in a seed-mediationgrowth method.

Gold nanoshells (comprising a silica core around 100 nm with a thinshell of gold a few nanometers thick) and gold nanocages may also beproduced. Gold nanospheres, nanorods, nanostars and nanoshells may beused as contrast agents according to various embodiments.

According to an embodiment gold nanoparticles may be used for cancerimaging. It is known that gold nanoparticles scatter strongly and thescattering properties depend upon the size, shape and structure of thenanoparticles. According to an embodiment gold nanoparticles having adiameter 30-100 nm may be used. Such nanoparticles scatter intensely andcan be detected using a microscope under dark field illuminationconditions.

The gold nanoparticles may be conjugated with, for example,anti-epidermal growth factor receptors (anti-EGFR) antibodies (or otherantibodies) to recognise the EGFR proteins (or other proteins) of cancercells and tissues. The regular or well organised scattering pattern ofnanoparticles bound to cancer cells can be readily distinguished fromthe random distribution of nanoparticles around healthy cells and thisdifference in scattering pattern may be utilised according to variousembodiments.

The nanoparticles may be excited by white light from a halogen lamp.

According to an embodiment, functionalised gold nanoparticles may bedistributed across the surface of a target (such as biological in vivoor ex vivo tissue) and the gold nanoparticles may preferentially bind tocancerous cells. As a result, cancerous regions of tissue can beidentified by illuminating the target and either analysing thescattering pattern or measuring the scattered intensity of light.

For example, gold nanoparticles may have a strong surface plasmonresonance (“SPR”) around 540 nm on the cell monolayer with the resultthat the nanoparticles scatter strongly in the green to yellow range ofthe visible spectrum. Similarly, gold nanorods may be constructed whichexhibit a strong surface plasmon resonance (“SPR”) around 800 nm givingan intense red colour.

Accordingly, gold nanoparticles may be used as imaging, physical orchemical contrast agents according to various embodiments.

Surface plasmon resonance (“SPR”) effects also enhance the Ramanscattering of adjacent molecules because the Raman intensity is directlyproportional to the square of the field intensity imposed on themolecules. This phenomenon is termed as surface enhanced Ramanscattering (“SERS”).

According to an embodiment gold nanoparticles may be utilised in orderto enhance Raman scattering of adjacent molecules. The goldnanoparticles may be either symmetric or asymmetric. According to anembodiment the gold nanoparticles may be asymmetric (e.g. nanorods)since asymmetric nanoparticles provide a larger Raman enhancement due tothe lightening rod effect.

One particular advantage of using gold nanoparticles and surface enhanceRaman scattering is that this approach greatly enhances detectionsensitivity and decreases signal acquisition time.

According to another embodiment a Raman tag may be used as aspectroscopic imaging probe. The Raman tag may comprise organic dyemolecules with aromatic structures which have relatively high Ramancross sections. Its fluorescence is quenched when they are adsorbed onto metallic nanoparticles and thus Raman signals are able to bedetected.

The Raman tags may be physically adsorbed or chemically conjugated withboth Raman tag and cancer targeting ligands.

According to other embodiments levan nanoparticles may be utilised fortargeted cancer imaging. Levan is a biocompatible carbohydrate polymerthat consists of β-D-fructofuranose attached by β-(2,6) linkages and isused in biomedical applications. According to an embodiment Indocyaninegreen (ICG) may be encapsulated in levan nanoparticles by self-assemblyand the levan-ICG nanoparticles may be used for cancer imaging.

Various embodiments are contemplated wherein a target which may comprisebiological tissue may be subjected to Raman or laser imaging(transmission or fluorescence) using nanoparticles such as goldnanoparticles are described above as contrast agents. One or moreregions of interest may then be identified and the regions of interestmay then be subjected to analysis using a first device to generateaerosol, smoke or vapour. The first device may comprise an ambientionisation ion source such as a rapid evaporative ionisation massspectrometry (“REIMS”) ion source.

Other embodiments are contemplated wherein chemical tags (such asluminescent tags) may be used in combination with an ambient ionisationion source such as a rapid evaporative ionisation mass spectrometry(“REIMS”) ion source. For example, according to an embodiment aluminescent imaging, physical or chemical contrast agent may be modifiedwith the inclusion of a ligand that is readily ionisable by an ambientionisation ion source such as a rapid evaporative ionisation massspectrometry (“REIMS”) ion source. The contrast agents, tags ornanoparticles may be detected by mass spectrometry if an undesired (ordesired) target or undesired (or desired) tissue is ablated. The taggingchemical may have fluorescent, magnetic, chemical, physical or otherimaging properties and a part of the molecule may be arranged so as toionise well for mass spectrometry analysis. For example, as describedabove, Indocyanine green (ICG) may be encapsulated into levannanoparticles or more generally in functionalised nanoshells which arefunctionalised so as to target cancerous tissue or other undesiredtarget material. Embodiments are contemplated wherein ICG (or otherchemicals) which may be encapsulated within functionalised nanoparticlesor nanoshells (which may be functionalised so as to target canceroustissue) may be detected by mass spectrometry. Other embodiments arecontemplated wherein one or more different markers other than ICG may beencapsulated into nanoparticles which target cancerous tissue. These oneor more markers may then identified by mass spectrometry and adetermination may be made that the tissue which is currently beinganalysed comprises cancerous tissue or otherwise comprises undesiredtarget material.

Embodiments are contemplated wherein target experiments may be performedwherein a target is subjected to mass spectrometry analysis with a viewto seeking to identify portions of target or tissue which include (orconversely do not include) a contrast agent, chemical tag, marker ornanoparticle wherein the contrast agent, chemical tag, marker ornanoparticle has been functionalised so as to target a particular targete.g. cancerous tissue. According to various embodiment identifying thepresence of the contrast agent, chemical tag, marker or nanoparticlethereby enables a determination to be made that the target or tissuewhich is currently being analysed comprises cancerous tissue (orotherwise desired or undesired target material).

According to an embodiment the step of using physical or other non-massspectrometric data to determine one or more regions of interest maycomprise the use of targeted nanoparticles containing or comprising ametal which is intended to change the electrical impedance of a targetedtissue type. As detailed above, metallic nanoparticles may befunctionalised so that they adhere to specific types of tissue or othersurfaces. One or more regions of interest of a target may be identifiedby determining one or more regions of a target (e.g., tissue) having adifferent impedance to other target areas due to the presence oftargeted or functionalised nanoparticles which preferentially adhere tocertain specific target areas (e.g., cancerous tissue).

Photothermal Therapy (PTT)

Gold nanoparticles absorb light much more strongly than organic dyemolecules. Nearly 100% adsorbed light is converted to heat vianonradiative properties. Accordingly, gold nanoparticles may be used asphotothermal contrast agents for photothermal therapy wherein photonenergy is converted to heat sufficient to induce cellular damage viathermal effects such as hyperthermia, coagulation and evaporation.

Photothermal therapy may be performed using spherical gold nanoparticlesin conjunction with either pulsed or continuous wave lasers.

Nanosecond pulsed lasers may be used in conjunction with PTT to providehighly selective and localised damage to cancer cells without affectingneighbouring healthy cells which may be only a few nanometers to tens ofmicrometers away.

For in vivo therapy of tumours under the skin or deeply seated tumourswithin tissue near infrared (NIR) light may be used because of its deeppenetration ability due to minimal absorption by hemoglobin and watermolecules.

According to an embodiment PEGylated gold nanoshells may used inconjunction with an ambient ionisation ion source since the absorptionof gold nanoshells can be tuned to the NIR region. A continuous wave(cw) diode laser e.g. emitting at 820 nm with an irradiance of e.g. 35W/cm² for 4 mins may be used to illuminate the gold nanoshells in orderto cause cancer cell death of targeted cells.

The gold nanoshells may according to various embodiments be injectedinto the blood stream of a patient or spread upon the surface of atarget or tissue sample.

Other embodiments are contemplated wherein PTT may be performed usinggold nanorods. According to an embodiment a cw Ti:Saphhire laseremitting at 800 nm may be used in conjunction with gold nanorods.

According to an embodiment the target may be illuminated with eitherlinearly polarized light or circularly polarized light. Illuminatinggold nanorods with circularly polarized light is particularly beneficialas the light absorption by gold nanorods is enhanced leading to anultra-low energy threshold for cancer killing.

It has been determined that a laser fluence of 30 J/cm² can result in anincrease in temperature of the cells by about 10° C. which is sufficientto induce heat-stress cell death. Accordingly, a laser fluence of 30J/cm² may be utilised according to various embodiments.

According to an embodiment gold nanorods may be conjugated tomethoxy-poly (ethylene-glycol)-thiol having an average MW 5,000(mPEG-SH-5000) and may be injected into a patient either intravenouslyand/or subcutaneously. Tumours or cancerous cells can be identifiedusing transmission imaging of a NIR laser with a camera due to the NIRlight absorption by the nanorods in the tumour.

Combination of Raman Spectroscopy with Rapid Evaporative Ionisation MassSpectrometry (“REIMS”) and other ambient ionisation techniques for thein situ identification of tumours During Surgery

According to an embodiment Raman spectroscopy may be combined with rapidevaporative ionization mass spectrometry (“REIMS”) (or other ambientionisation techniques) for the identification of tumours either duringsurgery or when analysing ex vivo tissue. Experimental data is presentedbelow taken from the context of in vivo brain surgery. However, theapproach of combining Raman spectroscopy with ambient ionisationtechniques such as rapid evaporative ionization mass spectrometry(“REIMS”) may be applied to other situations including other types ofsurgery and non-surgical applications.

A sampling and validation method is summarized in FIG. 15. According toan embodiment one or more Raman sampling points may be identified. Ramansampling may then be performed at the sampling points. Localisation ofthe one or more Raman sampling points may then be performed using a 3Din vivo ultrasonic visualisation system.

Rapid evaporative ionisation mass spectrometry (“REIMS”) sampling (orsampling using a different type of ambient ionisation ion source) maythen be performed in vivo from exactly the same locations as the Ramansampling points. Furthermore, a biopsy sample may optionally be takenfrom the area for histological validation.

The target (e.g. surgical site) may first be sampled by Ramanspectroscopy, followed by an ultrasonic reading and localization of thearea. As a subsequent step rapid evaporative ionisation massspectrometry (“REIMS”) sampling (or another method of ambientionisation) may then be performed using e.g. bipolar forceps or a laserablation device. The rapid evaporative ionisation mass spectrometry(“REIMS”) sampling (or other method of ambient ionisation) may then befollowed by taking a core biopsy of the area for ex vivo analysis andhistopathology.

According to an embodiment a number of different sampling points may beused during a surgical procedure. For example, according to anexperiment which was performed and which is described in more detailbelow, 14 sampling points were used. However, it will be understood tothose skilled in the art and a fewer or greater number of samplingpoints may be used.

A total of 24 patients were enrolled in one particular patient studyinvolving rapid evaporative ionisation mass spectrometry (“REIMS”)analysis of brain tumours during which additional Raman sampling wasperformed in nine cases.

FIG. 16 relates to a case study of one out of the 24 patients who wereall suffering from different types of brain tumours. The particularpatent who was the subject of the case study presented in FIG. 16 waspatient #4 (IKBRA04) who had grade IV Glioblastoma multiforme (“GBM”). Afull list of patients and their associated tumour type is given in thefollowing table:

Patient Tumour type WHO grade IKBRA01 low grade oligodendroglioma GradeII IKBRA02 low grade fibrillary astrocytoma Grade II IKBRA03 Anaplasticastrocytoma Grade III IKBRA04 Glioblastoma multiforme Grade IV IKBRA05Glioblastoma multiforme Grade IV IKBRA06 Diffuse astrocytoma IKBRA07Anaplastic astrocytoma Grade III IKBRA08 Meningioma Grade I IKBRA09Cystic gliosarcoma IKBRA10 Anaplastic oligodendroglioma Grade IIIIKBRA11 Glioblastoma multiforme Grade IV IKBRA12 Glioblastoma multiformeGrade IV IKBRA13 Fibrillary and gemistocytic Grade II astrocytomaIKBRA14 Diffuse astrocytoma Grade II IKBRA15 Ependymoma, cellular typeGrade II IKBRA16 Glioblastoma multiforme Grade IV IKBRA17 Glioblastomamultiforme Grade IV IKBRA18 Oligodendroglioma Grade II IKBRA19 GiantCell Glioblastoma Grade IV IKBRA20 Anaplastic astrocytoma Grade IIIIKBRA21 Low grade astrocytoma Grade II IKBRA22 Low grade astrocytomaGrade II IKBRA23 Recurrent glioblastoma Grade IV IKBRA24 Anaplasticastrocytoma Grade III

The left-hand portion of FIG. 16 shows a 3D image of the brain ofpatient #4 which has been overlayed with a real time ultrasonic image.Six sampling points were taken using a rapid evaporative ionisation massspectrometry (“REIMS”) probe during surgery and are also depicted on theimage shown in FIG. 16.

FIG. 16 also shows six corresponding mass spectra which were recordedwherein each mass spectrum corresponds to a different sampling point.

FIG. 16 also shows a 3D PCA plot of all sampling point taken during thesurgery. The 3D PCA plot was labelled by a neuropathologist.

All in vivo and ex vivo sampling points are shown on the PCA plot shownin FIG. 16. It is apparent from FIG. 16 that normal grey and whitematter group separately both from the cancerous samples and from eachother.

Tumour Typing and Grading Using a Rapid Evaporative Ionisation MassSpectrometry (“REIMS”) Probe

FIG. 17 shows the result according to an embodiment of comparingpatients with high grade (grade IV) Glioblastoma multiforme (e.g.,Glioblastoma, giant cell Glioblastoma and recurrent Glioblastoma) andlow grade (grade II and III) tumours (e.g. anaplastic astrocytoma,oligodendroglioma and diffuse astrocytoma).

It is apparent from FIG. 17 that high grade (grade IV) and low grade(grade II and III) tumours separated well on a 3D pseudo LDA plot.

Patients having intermediate grade III tumours grouped either with thehigh grade area of the space or with the low grade area of the space.

Embodiments are contemplated wherein the positioning of a sample in the3D space may be used to predict the possible progression of ananaplastic astrocytoma in the future.

Comparison of Healthy and Cancerous Samples with Both Raman Spectroscopyand Rapid Evaporative Ionisation Mass Spectrometry (“REIMS”) Sampling

Patient #21 (IKBRA21) was suffering from a low grade (grade II)astrocytoma. The patient was subjected to a combination of Ramanspectroscopy sampling and rapid evaporative ionisation mass spectrometry(“REIMS”) sampling. Raman data from a total of 32 sampling points wererecorded. 13 of these 32 sampling points corresponded with normaltissue, 18 of these 32 sampling points corresponded with canceroustissue and 1 corresponded with background.

Rapid evaporative ionisation mass spectrometry (“REIMS”) sampling wasalso performed at 14 of the 32 sampling points.

FIG. 18 shows rapid evaporative ionisation mass spectrometry (“REIMS”)mass spectra from two sampling points. Sampling point S4 correspondedwith tumour tissue having a low cellularity. In particular, samplingpoint S4 corresponded with posterior medial superficial tumour.Fragments of the tumour tissue had low cellularity and some degree ofreactive gliosis. Sampling point S14 corresponded with normal whitematter have single cell infiltration. In particular, sampling point S14corresponded with posterior base pot. Multiple fragments of white matterwith reactive gliosis and single-cell tumour infiltration are present.

FIG. 18 also shows a 3D PCA plot corresponding to all sampling pointstaken throughout the surgery.

FIG. 19 shows corresponding Raman spectra from sampling points S4(tumour) and S14 (normal white matter) together with a 3D PCA plot fromall sampling points taken throughout the surgery.

Both the Raman spectra and mass spectra obtained using an ambientionisation ion source such as a rapid evaporative ionisation massspectrometry (“REIMS”) ion source have a tissue specific “fingerprint”in the phospholipid range. The main differences observed on the PCA plotare due to the lipid vibration region.

There are a number of sulfatides which are very specific for normalwhite matter of brain. For example, the following sulfatides arespecific for normal white matter of the brain:

m/z (calculated) compound formula 888.624 C24:1 sulfatide C₄₈H₉₁NO₁₁S906.635 C24-OH sulfatide C₄₈H₉₂NO₁₂S 916.655 C26:1 sulfatide C₅₀H₉₄NO₁₁S

The above described embodiments represent a novel protocol forintraoperative tissue identification and validation in surgicalapplications wherein both rapid evaporative ionisation mass spectrometry(“REIMS”) technology and Raman spectroscopy are utilised. The variousembodiments disclosed above show that both technologies are feasible forthe distinction of healthy tissue and different brain cancers during anoperation.

Raman spectroscopy, used as a non-invasive probe, is particularlysuitable for providing initial information to a surgeon about where tostart cutting, operating or resecting.

Rapid evaporative ionisation mass spectrometry (“REIMS”) can providemore detailed and continuous information about the dissected tissue andmay also be used to predict if a low grade tumour (e.g., grade II orIII) has a high likelihood of progressing to a high grade tumour (e.g.,grade IV) in the future or not.

The combination of Raman spectroscopy and rapid evaporative ionisationmass spectrometry (“REIMS”) technologies enables molecular navigation inreal-time and the combination of these two technologies enablesimportant information to be provided to a surgeon in the assessment oftumour margins and tumour types (which can lead to an increase in thesurvival rate of patients).

Multivariate Analysis of Chemical Data

Various further embodiments are contemplated wherein the chemical datamay itself be subjected to multivariate analysis in order to assist, forexample, in the identification of the target and/or to filter outoutliers.

Methods of Medical Treatment, Surgery and Diagnosis and Non-MedicalMethods

Various different embodiments are contemplated. According to someembodiments the methods disclosed above may be performed on in vivo, exvivo or in vitro tissue. The tissue may comprise human or non-humananimal tissue. Embodiments are contemplated wherein the target maycomprise biological tissue, a bacterial or fungal colony or moregenerally an organic target such as a plastic).

Various embodiments are contemplated wherein analyte ions generated byan ambient ionisation ion source are then subjected either to: (i) massanalysis by a mass analyser such as a quadrupole mass analyser or a Timeof Flight mass analyser; (ii) ion mobility analysis (IMS) and/ordifferential ion mobility analysis (DMA) and/or Field Asymmetric IonMobility Spectrometry (FAIMS) analysis; and/or (iii) a combination offirstly (or vice versa) ion mobility analysis (IMS) and/or differentialion mobility analysis (DMA) and/or Field Asymmetric Ion MobilitySpectrometry (FAIMS) analysis followed by secondly (or vice versa) massanalysis by a mass analyser such as a quadrupole mass analyser or a Timeof Flight mass analyser. Various embodiments also relate to an ionmobility spectrometer and/or mass analyser and a method of ion mobilityspectrometry and/or method of mass analysis. Ion mobility analysis maybe performed prior to mass to charge ratio analysis or vice versa.

Various references are made in the present application to mass analysis,mass analysers, mass analysing, mass spectrometric data, massspectrometers and other related terms referring to apparatus and methodsfor determining the mass or mass to charge of analyte ions. It should beunderstood that it is equally contemplated that the present inventionmay extend to ion mobility analysis, ion mobility analysers, ionmobility analysing, ion mobility data, ion mobility spectrometers, ionmobility separators and other related terms referring to apparatus andmethods for determining the ion mobility, differential ion mobility,collision cross section or interaction cross section of analyte ions.Furthermore, it should also be understood that embodiments arecontemplated wherein analyte ions may be subjected to a combination ofboth ion mobility analysis and mass analysis i.e. that both (a) the ionmobility, differential ion mobility, collision cross section orinteraction cross section of analyte ions together with (b) the mass tocharge of analyte ions is determined. Accordingly, hybrid ionmobility-mass spectrometry (IMS-MS) and mass spectrometry-ion mobility(MS-IMS) embodiments are contemplated wherein both the ion mobility andmass to charge ratio of analyte ions generated e.g. by an ambientionisation ion source are determined. Ion mobility analysis may beperformed prior to mass to charge ratio analysis or vice versa.Furthermore, it should be understood that embodiments are contemplatedwherein references to mass spectrometric data and databases comprisingmass spectrometric data should also be understood as encompassing ionmobility data and differential ion mobility data etc. and databasescomprising ion mobility data and differential ion mobility data etc.(either in isolation or in combination with mass spectrometric data).

Various surgical, therapeutic, medical treatment and diagnostic methodsare contemplated.

However, other embodiments are contemplated which relate to non-surgicaland non-therapeutic methods of mass spectrometry which are not performedon in vivo tissue. Other related embodiments are contemplated which areperformed in an extracorporeal manner such that they are performedoutside of the human or animal body.

Further embodiments are contemplated wherein the methods are performedon a non-living human or animal, for example, as part of an autopsyprocedure.

Although the present invention has been described with reference topreferred embodiments, it will be understood by those skilled in the artthat various changes in form and detail may be made without departingfrom the scope of the invention as set forth in the accompanying claims.

1. A method comprising: obtaining or acquiring chemical or othernon-mass spectrometric data from one or more regions of a target,wherein said chemical or other non-mass spectrometric data comprisesfluorescence data; using said chemical or other non-mass spectrometricdata to determine one or more regions of interest of said target; usinga first device to generate aerosol, smoke or vapour from one or moreregions of said target; and mass analysing and/or ion mobility analysingsaid aerosol, smoke or vapour or ions derived from said aerosol, smokeor vapour in order to obtain mass spectrometric data and/or ion mobilitydata.
 2. (canceled)
 3. (canceled)
 4. A method as claimed in claim 1,wherein said first device comprises or forms part of an ambient ion orionisation source or wherein said first device generates said aerosol,smoke or vapour for subsequent ionisation by an ambient ion orionisation source or other ionisation source.
 5. A method as claimed inclaim 1, wherein said target comprises native or unmodified targetmaterial.
 6. A method as claimed in claim 5, wherein said native orunmodified target material is unmodified by the addition of a matrix orreagent.
 7. A method as claimed in claim 1, wherein said first device isarranged and adapted to generate aerosol, smoke or vapour from one ormore regions of said target without said target requiring priorpreparation.
 8. A method as claimed in claim 1, wherein said firstdevice comprises an ion source selected from the group consisting of:(i) a rapid evaporative ionisation mass spectrometry (“REIMS”) ionsource; (ii) a desorption electrospray ionisation (“DESI”) ion source;(iii) a laser desorption ionisation (“LDI”) ion source; (iv) a thermaldesorption ion source; (v) a laser diode thermal desorption (“LDTD”) ionsource; (vi) a desorption electro-flow focusing (“DEFFI”) ion source;(vii) a dielectric barrier discharge (“DBD”) plasma ion source; (viii)an Atmospheric Solids Analysis Probe (“ASAP”) ion source; (ix) anultrasonic assisted spray ionisation ion source; (x) an easy ambientsonic-spray ionisation (“EASI”) ion source; (xi) a desorptionatmospheric pressure photoionisation (“DAPPI”) ion source; (xii) apaperspray (“PS”) ion source; (xiii) a jet desorption ionisation(“JeDI”) ion source; (xiv) a touch spray (“TS”) ion source; (xv) anano-DESI ion source; (xvi) a laser ablation electrospray (“LAESI”) ionsource; (xvii) a direct analysis in real time (“DART”) ion source;(xviii) a probe electrospray ionisation (“PESI”) ion source; (xix) asolid-probe assisted electrospray ionisation (“SPA-ESI”) ion source;(xx) a cavitron ultrasonic surgical aspirator (“CUSA”) device; (xxi) afocussed or unfocussed ultrasonic ablation device; (xxii) a microwaveresonance device; and (xxiii) a pulsed plasma RF dissection device.9-24. (canceled)
 25. A method as claimed in claim 1, wherein said targetcomprises biological tissue, biological matter, a bacterial colony or afungal colony. 26-49. (canceled)
 50. A method as claimed in claim 1,further comprising directing light or ultra-violet radiation on to saidtarget.
 51. A method as claimed in claim 50, wherein said ultra-violetradiation has a wavelength in a range selected from the group consistingof: (i) 100-150 nm; (ii) 150-200 nm; (iii) 200-250 nm; (iv) 250-300 nm;(v) 300-350 nm; and (vi) 350-400 nm.
 52. A method as claimed in claim 50or 51, further comprising detecting light or electromagnetic radiationemitted from said target.
 53. A method as claimed in claim 52, furthercomprising determining a fluorescence or autofluorescence profile orspectrum.
 54. A method as claimed in claim 53, wherein said fluorescenceor autofluorescence profile or spectrum comprises a measure of theintensity of light or electromagnetic radiation emitted from said targetas a function of frequency or wavelength.
 55. A method as claimed inclaim 1, further comprising comparing a fluorescence or autofluorescenceprofile or spectrum relating to a region of said target with afluorescence or autofluorescence profile or spectrum obtained from acontrol sample, a control region, control data or predetermined data inorder to determining one or more regions of interest of said target.56-69. (canceled)
 70. A method as claimed in claim 1, further comprisingusing said chemical or other non-mass spectrometric data to determinethe margins or bounds of one or more regions of interest of said target.71-73. (canceled)
 74. A method as claimed in claim 1, further comprisingusing one or more contrast agents to enhance said chemical data.
 75. Amethod as claimed in claim 74, wherein said one or more contrast agentscomprise one or more fluorescent contrast agents. 76-87. (canceled) 88.A method of mass spectrometry and/or ion mobility spectrometrycomprising a method as claimed in claim
 1. 89. Apparatus comprising: adevice arranged and adapted to obtain chemical or other non-massspectrometric data from one or more regions of a target, wherein saidchemical or other non-mass spectrometric data comprises fluorescencedata; a control system arranged and adapted to use said chemical orother non-mass spectrometric data to determine one or more regions ofinterest of said target; a first device for generating aerosol, smoke orvapour from one or more regions of said target; and a mass analyserand/or ion mobility analyser for mass analysing and/or ion mobilityanalysing said aerosol, smoke or vapour or ions derived from saidaerosol, smoke or vapour in order to obtain mass spectrometric dataand/or ion mobility data. 90-171. (canceled)
 172. An ambient ionisationion source comprising apparatus as claimed in claim
 89. 173-174.(canceled)
 175. A mass spectrometer and/or ion mobility analysercomprising apparatus as claimed in claim 89 176-197. (canceled)